A method for modeling and fault simulation of an aero-engine lubricating oil system

Abstract

The present application relates to a kind of modeling and fault simulation method for aero-engine lubricating oil system, it is related to aerospace technical field.The present application includes four systems of oil supply subsystem, oil return subsystem, ventilation system and thermal system, first, component model is established, then ventilation, oil supply, oil return and thermal subsystem model are established, finally, lubricating oil whole system simulation model is constituted.The present application can obtain accurate and reliable lubricating oil system numerical simulation model, and realizes lubricating oil system fault simulation function by analyzing the system parameter change caused by failure, provides support for lubricating oil system optimization design and health management, and it has important significance to China's aero-engine technology research.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of aerospace technology, in particular to a method for modeling and simulating faults of an aero-engine lubricating oil system, which is suitable for aero-engine modeling simulation and fault diagnosis. BACKGROUND

[0002] With the development of advanced aero-engine technology, the position of its lubricating oil system is becoming more and more prominent, and it has become the focus of research by major engine research institutions. The lubricating oil system is an important accessory for ensuring the normal operation of the engine, and is also an important way to obtain engine health information, and plays an important role in engine health management.

[0003] Currently available information includes: Su Li et al. studied the numerical simulation of the oil pressure of the oil supply subsystem under the commercial software Flowmaster in "Simulation and Calculation of Oil Pressure of Aero-Engine Lubricating System"; Zhu Pengfei et al. studied the modeling of flow and heat transfer of liquid pipeline under MATLAB / Simulink in "Simulation Platform for Flow and Heat Transfer of Aero-Engine Pipeline System"; Liu Zhenxia et al. studied the calculation of flow and heat transfer of the oil supply and return subsystem in "Development of General Analysis Software for Aero-Engine Lubricating System"; Yu Li et al. studied the calculation method of bearing cavity pressure of the venting system in "Calculation Method of Bearing Cavity Pressure of Aero-Engine with Throttling Ventilation"; Liu Bo et al. studied the steady-state model of the lubricating oil system in "Construction of Steady-State Model of Aero-Engine Lubricating Oil System", but the bearing cavity pressure needs to be obtained through assumptions and empirical formulas, which may cause calculation errors.

[0004] The above documents mainly study the lubricating oil subsystem model. The modeling of such a complex aero-engine lubricating oil system is difficult, has a long development cycle, lacks research on full-system modeling, and the model established by professional software such as Flowmaster is difficult to realize collaborative simulation and on-board real-time calculation. MATLAB / Simulink software contains automatic code generation function, which can easily convert the established MATLAB / Simulink model into C language for on-board real-time calculation, and has better flexibility and adaptability. SUMMARY

[0005] Technical problems to be solved

[0006] To address the challenge of achieving subsystem co-simulation and real-time airborne computation in aero-engine lubricating oil system models based on specialized software like Flowmaster, this invention provides a MATLAB / Simulink-based method for modeling and simulating the faults of aero-engine lubricating oil systems. First, component models are established, followed by models of ventilation, oil supply, oil return, and thermal subsystems, ultimately forming a complete lubricating oil system simulation model. This invention yields an accurate and reliable numerical simulation model of the lubricating oil system and, by analyzing system parameter changes caused by faults, enables fault simulation of the lubricating oil system. This provides support for the optimized design and health management of lubricating oil systems and is of significant importance to aero-engine technology research in my country.

[0007] Technical solution

[0008] The technical solution adopted by the present invention to solve its technical problem includes the following steps:

[0009] Step 1: Modeling the oil supply subsystem.

[0010] This step consists of two parts: modeling typical components and modeling the subsystem iterative algorithm and the fuel supply system.

[0011] For component 1 of the oil supply system, the oil pump, the theoretical formula for calculating the pump flow rate is:

[0012] Q p理论 =N p ·V=N2i·V(1)

[0013] In the formula N p N1 and N2 are the pump speed and high-pressure rotor speed, respectively, in rpm. i is the transmission ratio between the engine high-pressure shaft and the fuel pump shaft, i.e., N p = N2·i, where V is the pump displacement. The actual flow rate of the oil supply pump is also affected by the volumetric efficiency η. v Impact:

[0014] Q p实际 =Q p理论 η v (2)

[0015] For the oil supply system component 2, the oil supply pipeline model, the oil supply pipeline resistance Δp a The calculation formula is as follows:

[0016]

[0017] In the formula L a For pipe length, d a v is the inner diameter of the pipe. a Let f be the flow velocity, ρ be the density of the lubricating oil, and f be the flow rate. a The coefficient of friction is given by [formula missing], and for viscous liquids such as lubricating oil, it is calculated as [formula missing]. The calculation of Reynolds number Re is shown in the following formula

[0018]

[0019] In the formula, v a is the flow rate, d a is the inner diameter of the pipe, and p and m are the density and kinematic viscosity of the lubricating oil. The relationship between the kinematic viscosity of the lubricating oil m and the temperature t is lnln(m+A) = B-Cln(t+273).

[0020] For the oil supply filter model of the oil supply system component 3, the oil filter resistance Ap b The theoretical calculation formula is shown in the following formula:

[0021] Ap b = Ap b1 + Ap b2 = K'X1V b 2 p / 2+X2V b 2 p / 2 (5)

[0022] In the formula, Ap b1 is the filter resistance, Ap b2 is the shell inlet resistance loss, K' is the Reynolds number influence correction coefficient, V b is the liquid flow velocity on the entire area of the mesh, X1 is the filter resistance coefficient, X2 is the local resistance coefficient at the shell inlet, and p is the density of the lubricating oil.

[0023] The oil filter resistance characteristics are obtained by using the test data fitting method, so it is necessary to determine the relationship between the flow resistance and the flow rate, which is shown in the following formula:

[0024]

[0025] In the formula, X = K'X1+X2, Q b is the lubricating oil flow rate, unit: L / min, A b is the oil filter mesh cross-sectional area, unit: m 2 .

[0026] The oil supply filter resistance characteristic calculation formula is set as:

[0027] Ap b = k b Q b 2 (Pa) (7)

[0028] In the formula, Q b is the lubricating oil flow rate, unit: L / min, and k bThe oil filter resistance characteristic coefficient is k, and the oil filter resistance characteristic test data is known. The relationship between flow resistance loss and oil flow is fitted by using the Polynomial polynomial fitting function of the cftool toolbox in MATLAB according to the test data to obtain k b .

[0029] The oil filter has a differential pressure switch quantity sensor. When the differential pressure of the oil filter is too large, the differential pressure switch quantity changes, and is used to indicate that the oil filter is blocked. The threshold value is a known parameter, so the oil filter model needs to output the differential pressure switch quantity in addition to calculating the flow resistance. The differential pressure switch quantity “1” represents that the oil filter is blocked, and “0” represents that the oil filter is not blocked.

[0030] For the flow resistance model of the servo fuel heater and the fuel oil radiator of the oil supply system component 4, the flow resistance characteristic calculation formulas of the two heat exchangers are as follows:

[0031] ΔP s = ΔP0φd0+ ΔP ip + ΔP Ns (8)

[0032] Wherein ΔP s is the radiator pressure drop, ΔP0 is the tube bundle pressure drop, ΔP ip is the guide plate pressure drop, and ΔP Ns is the shell inlet nozzle pressure drop. The calculation method of each part of the pressure drop is as follows:

[0033]

[0034]

[0035]

[0036] In the formula, V0 is the mass flow rate of the shell flow, kg / (m 2 ·s); V Ns is the mass flow rate at the outlet and inlet of the shell guide plate, kg / (m 2 ·s); ξ0 is the friction resistance coefficient of the circular tube of the shell flow; φ0 is the viscosity correction coefficient of the shell flow; ρ s is the density of the shell flow, unit: kg / m 3 ; D s is the inner diameter of the shell, unit: m; n b is the number of baffle plates; d e is the equivalent diameter of the shell, unit: m; and ξ ip is the resistance coefficient of the guide plate.

[0037] The resistance characteristics Δp c1 of the servo fuel heater and the resistance characteristics Δp c2 of the fuel oil radiator are calculated as follows:

[0038] Δp c1 =k c1 Q c 2 (Pa) (12)

[0039] Δp c2 =k c2 Q c 2 (Pa) (13)

[0040] wherein Q c is the flow rate of the oil, in L / min, k c1 is the resistance characteristic coefficient of the servo fuel heater, k c2 is the resistance characteristic coefficient of the fuel-oil radiator, according to known resistance characteristic test data, using the Polynomial polynomial fitting function of the cftool toolbox in MATLAB, the relationship between flow resistance loss and oil flow rate is fitted according to the test data to obtain k c1 , k c2 .

[0041] For the oil supply system component 5, the oil nozzle flow rate model is divided into a nozzle physical model and a nozzle iterative calculation module.

[0042] The oil nozzle flow rate calculation formula of the nozzle flow rate physical model is as follows:

[0043]

[0044] wherein Q d is the flow rate of the nozzle, in L / min; C d is the flow coefficient; d d is the nozzle aperture, in mm; Δp d is the difference between the front pressure and the back pressure of the nozzle, in bar; and ρ is the oil density, in g / cm 3 .

[0045] The iterative algorithm module of the nozzle is established by inputting the initial set nozzle front pipeline inlet flow rate Q a_0 , the pressure at the nozzle front node P0, the oil density ρ and the oil viscosity μ, and the nozzle flow rate is Q d =f(P u ,P b ), the front pressure P u differs from the pressure at the pipeline node P0 by a pipeline loss Δp a , i.e. P u =Δp a +P0, and the pipeline loss is Δp a =f(Q a), the pipeline flow and the nozzle flow should satisfy the conservation Q d = Q a , otherwise the difference between the pipeline flow and the nozzle flow is reduced by half Q a = (Q a + Q d ) / 2, until the difference between the two is less than a threshold value.

[0046] For the bypass valve of the oil supply system component 6, the modeling of the valve is realized by comparing the total pressure drop with the opening pressure of the bypass valve through the switch module to open and close the bypass valve. If it is greater than, the bypass valve is opened, the valve opening identifier is set to 1, and the flow resistance is the valve opening pressure. If it is less than, the fuel oil radiator outlet pressure is output as the valve outlet pressure, and the valve opening identifier is set to 0.

[0047] For the oil supply system iteration module, first, the high-pressure rotor speed N2 is obtained from the engine speed sensor, and the oil supply pump outlet pressure P pump_out is set.

[0048] Secondly, the front bearing cavity pressure P d1 , the middle bearing cavity pressure P d2 , the rear bearing cavity pressure P d3 and the gear box pressure P d4 are input, and the oil supply system component 2 oil supply pipeline resistance Δp a , the oil system component 3 oil filter resistance Δp b , the oil supply system component 4 servo fuel heater resistance characteristic Δp c1 and the fuel oil radiator resistance characteristic Δp c2 are calculated according to formulas (3), (7), (12) and (13). u_4

[0049] P u_4 = P0-ΔP a -ΔP b -ΔP c1 -ΔP c2 (15)

[0050] Wherein, P0 is the atmospheric pressure, ΔP a is the oil supply pipeline resistance, Δp b is the oil filter resistance, Δp c2 is the fuel oil radiator resistance characteristic, and Δp c1 is the servo fuel heater resistance characteristic.

[0051] The rear bearing cavity nozzle front pressure P u_3 ​​

[0052] P u_3 = P u_4 - ΔP a (16)

[0053] where P u_4 is the pressure before the gear box nozzle, and ΔP a is the resistance of the oil supply pipeline.

[0054] The pressure before the middle bearing cavity nozzle P u_2 is

[0055] P u_2 = P u_3 - ΔP a (17)

[0056] where P u_3 is the pressure before the gear box nozzle, and ΔP a is the resistance of the oil supply pipeline.

[0057] The pressure before the front bearing cavity nozzle P u_1 is

[0058] P u_1 = P u_2 - ΔP a (18)

[0059] where P u_2 is the pressure before the gear box nozzle, and ΔP a is the resistance of the oil supply pipeline.

[0060] The front bearing cavity nozzle flow Q d1 , the middle bearing cavity nozzle flow Q d2 , the rear bearing cavity nozzle flow Q d3 , and the gear box nozzle flow Q d4 of the oil supply system are calculated in sequence by formula (14) and the nozzle iteration algorithm, and the total oil supply amount Q d_all of the nozzle is obtained, that is

[0061] Q d_all = Q d1 + Q d2 + Q d3 + Q d4 (19)

[0062] where Q d1 is the front bearing cavity nozzle flow, Q d2 is the middle bearing cavity nozzle flow, Q d3 is the rear bearing cavity nozzle flow, and Q d4 is the gear box cavity nozzle flow.

[0063] Finally, the total oil supply amount Q d-all of the nozzle is compared with the pump flow to correct the pump outlet pressure, when the sum of the total fuel supply of the nozzles Q d-all is less than the pump flow rate , the pump outlet pressure P pump_out is increased, and vice versa, and the iteration is repeated until the difference between the two is within the allowable range. The iteration process of the fuel supply system is shown in Figure 1 .

[0064] Step 2: Modeling of the oil return subsystem.

[0065] This step includes two parts: modeling of typical components and establishment of the oil return system model.

[0066] For the oil return pump model, the normal working condition of the oil return system requires that the pump inlet pressure be greater than the minimum allowable pressure. The working condition is determined as shown in Figure 2 . When the pump inlet pressure after calculating the pressure loss of the gear or bearing is compared with the minimum allowable pressure by the switch module, if it is greater than the minimum allowable pressure, the normal working condition outputs the identifier "1", and vice versa, the output is "0".

[0067] For the oil return pipeline model, only the resistance characteristics are considered and the heat exchange characteristics are not considered, and only the friction loss is calculated and the local loss is not considered. The pipeline flow resistance calculation formula is:

[0068]

[0069] where Δp e is the two-phase flow pipeline loss, Δp g is the gas single-phase flow pipeline loss, is the correction coefficient.

[0070] The modeling method of the oil return filter is the same as that of the fuel supply filter. The calculation formula of the relationship between the oil return filter flow resistance and the oil return flow rate is:

[0071] Δp f = k3Q f 2 (21)

[0072] where Q f is the oil return flow rate, unit: L / min; k3 is the resistance characteristic coefficient of the oil return filter. According to the known oil return filter resistance characteristic test data, the relationship between the flow resistance loss and the oil flow rate is fitted using the Polynomial polynomial fitting function of the cftool toolbox in MATLAB to obtain k3.

[0073] There is a differential pressure switch sensor at the return oil filter to indicate oil filter blockage. When the differential pressure of the return oil filter exceeds a certain threshold, the differential pressure switch value changes. The threshold is a known parameter. Therefore, the return oil filter model outputs a differential pressure switch value, where "1" represents oil filter blockage and "0" represents no blockage. The selection is achieved through the switch module.

[0074] For the oil level model of component 4, the lubricating oil tank, given the initial lubricating oil volume, the calculation formula is used based on the cylinder volume V of the pipeline.

[0075] V=S×h (22)

[0076] Where S is the area of ​​the liquid bottom surface and h is the liquid level height or length.

[0077] The volume of each section of the oil supply and return system can be calculated sequentially. The sum of the volumes of each section of the pipeline is the amount of lubricating oil contained in the oil supply system pipeline. After obtaining the amount of lubricating oil contained in the oil supply and return pipelines and each component, the amount of lubricating oil in the oil tank can be calculated. Given that the oil tank is a cuboid, the oil level in the tank can be calculated according to the cuboid volume formula (22).

[0078] For the establishment of the iterative algorithm module for the oil return system, firstly, the oil tank pressure P is set. tank0 The nozzle flow rate Q in the front bearing cavity obtained in step one d1 Flow rate Q of nozzle in bearing cavity d2 , Rear bearing cavity nozzle flow rate Q d3 and gearbox nozzle flow rate Q d4 Oil supply Q to the front bearing cavity 前 Oil supply Q to the bearing cavity 中 Rear bearing cavity oil supply Q 后 and gearbox oil supply Q 齿 Therefore, the oil supply to each component is multiplied by the oil-air ratio γ. g Right now

[0079] Q′=Q×γ g (twenty three)

[0080] Where Q′ is the flow rate through each bearing, Q is the oil supply to each bearing, and γ g This refers to the oil-to-gas ratio.

[0081] Calculate the flow rates through the front bearing cavity, middle bearing cavity, rear bearing cavity, and gearbox using Q. all_回油 =Q 前′ +Q 中′ +Q 后′ +Q 齿′ The sum of the flow rates is the main loop flow rate Q. all_回油 .

[0082] Secondly, assume the main oil return path starting point pressure P 主回路 From the main oil return path starting point, according to formula (20), formula (21) in turn calculate the oil return system components 2 oil return pipeline pressure loss Δp e , component 3 oil return filter pressure loss Δp f , component 4 oil tank pressure P tank That is

[0083] P tank = P 主回路 - Δp e - Δp f (24)

[0084] Where P 主回路 is the main oil return path starting point pressure, Δp e is the oil return pipeline pressure loss, Δp f is the oil return filter pressure loss. Finally, compare the calculated pressure P tank of the oil tank with the set oil tank pressure P tank0 , if the difference is greater than the threshold, correct the oil return pump outlet pressure P 回油′ , if less than, stop iteration output main oil return pressure P 主回路 . The calculation process of the oil return pressure is shown in Figure 3 .

[0085] Step three, modeling of the ventilation system.

[0086] This step contains two parts, one is the modeling of typical components, and the other is the design of subsystem iteration algorithm and the modeling of the ventilation system.

[0087] For the ventilation system component 1 seal grate model, the seal leakage is calculated according to the seal gas pressure, temperature and bearing cavity pressure, and the grate seal gas leakage calculation formula is as follows:

[0088]

[0089] In the formula, m is the leakage mass flow, the unit is kg / s; is the flow area, the unit is m 2 ; T1 * is the gas temperature before the grate; is the leakage coefficient, and its calculation formula is:

[0090]

[0091] In the formula, t is the tooth tip thickness, the unit is m; c is the seal gap, the unit is m; N is the number of teeth; is the pressure before the grate, the unit is Pa; is the pressure after the grate, Pa; k, a is the empirical coefficient.​

[0092] For ventilation system component 2, the resistance characteristic Δp of the ventilation duct h The calculation formula is as follows:

[0093]

[0094] In the formula L h The length of the ventilation duct is expressed in meters (m); d h V is the inner diameter of the ventilation duct, in meters (m). h ρ0 represents the air velocity in the ventilation duct, in m / s; ρ0 represents the air density, in kg / m³. 3 ;f h The friction coefficient is affected by both the fluid and the pipe material, according to the Reynolds number Re. h The calculation method is as follows:

[0095]

[0096] The air density ρ0 is obtained from the ideal gas law.

[0097]

[0098] In the formula Let V0 be the ideal gas volume, n be the amount of gas, and t0 = -0.0059H. fly +18 is the Celsius temperature of the gas, R is the ideal gas constant 8.314 J / (mol·K), and M is the molar mass of air in g / mol.

[0099] For ventilation system component 3, the resistance characteristic Δp is obtained by fitting the axial ventilator. i The model is as follows:

[0100] Δp i =0.0148N3 + 579.1Q a -44.5 (kPa)(28)

[0101] In the formula, N3 is the low-pressure rotor speed, in rpm; Q a This is the mass flow rate of the ventilation gas, expressed in g / s.

[0102] The output of the grate leakage calculation is the mass flow rate, while the output of the ventilation duct flow resistance characteristic calculation is the volumetric flow rate. A conversion module for both flow rates is required to connect the grate sealing model and the ventilation duct. The calculation formula for the flow conversion module is shown below:

[0103]

[0104] In the above formula The volumetric flow rate is expressed in L / min. The mass flow rate is expressed in kg / s, and ρ is the gas density in kg / m³. 3 .

[0105] For the establishment of the iterative module of the ventilation system, firstly, for the design of the iterative algorithm of the ventilation system, the ventilation system model is a flow-pressure model. The iterative calculation in the model establishment can be divided into two parts: one is the pressure of the middle and rear bearing cavities, and the other is the pressure of each bearing cavity.

[0106] First, consider the pressure in the middle and rear bearing cavities. Since the pressure calculations for the middle and rear bearing cavities are similar, we first build and connect the component models according to the physical structure of the middle and rear bearing cavities. The iterative principle for the pressure in the middle cavity is pressure balance. First, input the temperature T1 before the toothed teeth are sealed. * Pressure before sealing the teeth Pressure after the fangs are sealed The parameters are: number of teeth N, sealing clearance c, flow area A, tooth tip thickness t, and set bearing cavity pressure P. 中 The gas leakage of the sealing grate of component 1 of the ventilation system is calculated according to formulas (25) and (26). Secondly, the ventilation resistance Δp from the middle bearing cavity to the front bearing cavity is calculated according to formula (27). h The pressure P in the bearing cavity is obtained from this. d2 Right now

[0107] P d2 =P d1 +Δp h (30)

[0108] Among them, P d1 The pressure in the front bearing cavity, Δp h This refers to the ventilation flow resistance from the middle bearing cavity to the front bearing cavity.

[0109] Finally, compare the bearing cavity pressure P. d2 Compared with the set bearing cavity pressure value P d2 If the difference is greater than the threshold, then the bearing cavity pressure P is corrected. d2 If the output is less than the bearing cavity pressure P, then stop the iteration and output the bearing cavity pressure. d2 Its calculation process is as follows: Figure 4 As shown.

[0110] Second, calculate the pressure in each bearing cavity. First, input the temperature T1 of each bearing cavity before the teeth are sealed. * Pressure before sealing the teeth Pressure after the fangs are sealed The parameters are: number of teeth N, sealing clearance c, flow area A, tooth tip thickness t, and pre-set bearing cavity pressure P. d1_0 , middle bearing cavity pressure P d2_0, rear bearing cavity pressure P d3_0 and gear box pressure P d4_0 , the sealing gas leakage amount of the ventilation system component 1 is calculated according to formula (25), formula (26) respectively Secondly, the ventilation flow resistance Δp h from the middle bearing cavity to the front bearing cavity is calculated according to formula (27) h , the ventilation flow resistance Δp h from the rear bearing cavity to the front bearing cavity is calculated according to formula (28) d2 , and the ventilation flow resistance Δp d3 from the gear box to the front bearing cavity is calculated according to formula (29) d4

[0111] P d2 = P1+ Δp h , P d3 = P1+ Δp h ', P d4 = P1+ Δp h " (31)

[0112] Wherein, P1 is the front bearing cavity pressure, Δp h is the ventilation flow resistance from the middle bearing cavity to the front bearing cavity, Δp h ' is the ventilation flow resistance from the rear bearing cavity to the front bearing cavity, and Δp h " is the ventilation flow resistance from the gear box to the front bearing cavity.

[0113] According to formula (28), formula (29), the resistance characteristics Δp i of the ventilation system component 3 shaft center ventilator are obtained, and the front bearing cavity pressure P d1 is calculated as

[0114] P d1 = P0+ Δp i (32)

[0115] Wherein, P d1 is the front bearing cavity pressure, P0 is the atmospheric pressure, and Δp i is the resistance characteristics of the shaft center ventilator.

[0116] Finally, the front bearing cavity pressure P d1 , the middle bearing cavity pressure P d2 , the rear bearing cavity pressure P d3 , and the gear box pressure P d4 are compared with the set front bearing cavity pressure P d1_0 , the set middle bearing cavity pressure P d2_0 , the set rear bearing cavity pressure P d3_0 , and the set gear box pressure P d4_0 , and if the difference is greater than a threshold value, the set front bearing cavity pressure Pd1_0 Mid bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 Gearbox pressure P d4_0 If less than, stop iteration output front bearing cavity pressure P d1 Mid bearing cavity pressure P d2 Rear bearing cavity pressure P d3 Gearbox pressure P d4 Ventilation system calculation process as shown in Figure 5

[0117] Step four, modeling of the thermal system.

[0118] This step contains two parts, one is the modeling of typical components, and the second is the design of the system iteration algorithm and the modeling of the oil supply system.

[0119] For the thermal system components 1 bearing, gear, the bearing, gear heat generation is obtained by linear interpolation of test data, the resulting calculation formula is as follows:

[0120] x bearing heat: H = A·N2-B (33)

[0121] In the formula, N2 is the high-pressure rotor speed, unit rpm; H is the corresponding component heat generation unit Kw; A, B values are obtained by interpolation calculation.

[0122] After obtaining the heat generation, the temperature rise of the oil flowing through the engine can be calculated, according to the formula:

[0123]

[0124] In the formula, H is the heating amount of all bearings and gears of the engine to the oil, unit KJ; C p is the specific heat capacity of the oil; m is the mass of the oil, unit kg.

[0125] For the thermal system components 2 oil tank, the oil tank exchanges heat with the outside environment, the oil exchanges heat with the tank in the form of heat conduction, and then the tank exchanges heat with the outside environment in the form of convection. The heat transfer calculation formula of the whole heat exchange process is as follows:

[0126]

[0127] In the formula, h1 is the thermal conductivity of air, δ is the thickness of the tank wall; t1 is the local atmospheric temperature, which is calculated according to the atmospheric temperature with height change data table in the literature; t2 is the inner wall temperature of the oil tank, A' is the heat transfer area, which is equal to the surface area of the oil tank in this case, λ is the tank thermal conductivity.

[0128] ​For the heat system components 3 servo fuel heater and fuel oil radiator, the oil system uses a shell and tube servo fuel heater and fuel oil radiator, the heat exchanger heat transfer characteristics test data interpolation to obtain the heat transfer efficiency η.

[0129] The heat transfer efficiency definition formula in the related test is as follows:

[0130]

[0131] In the formula, η is the heat transfer efficiency, T 滑入 is the inlet oil temperature of the radiator, T 燃入 is the inlet fuel temperature of the radiator, T 滑出 is the outlet oil temperature of the radiator.

[0132] For the heat system iterative algorithm modeling. Set an oil supply temperature T 滑出 , given the engine operating parameters are high pressure rotor speed N2, by formula (33) to calculate the three bearing heat generation H1, H2, H3, middle bearing cavity heat generation H4, rear bearing cavity heat generation H5, three gearboxes heat generation H6, H7, H8, the sum of heat generation through the bearing and gear is the engine heat generation H. Combined with the source return oil system to get the front bearing cavity flow Q 前 , middle bearing cavity flow Q 中 , rear bearing cavity flow Q 后 and gear box flow Q 齿 , and by formula (34) to calculate its flow through the engine temperature rise ΔT and then by formula to get the return oil temperature T 回油 after the oil flows through the heat generating components.

[0133] T 回油 = T 滑出 + ΔT (37)

[0134] Then according to formula (35) to calculate its heat dissipation φ in the oil tank, combined with the inlet fuel flow W of the radiator, the outlet oil temperature T 滑出 of the radiator to calculate the heat dissipation q

[0135] q = WC P (T 滑入 -T 滑出 ) (38)

[0136] Where, W is the inlet fuel flow of the radiator, C P is the specific heat capacity of the oil, the inlet fuel temperature T 滑入 of the radiator, T 滑出 is the outlet oil temperature of the radiator.

[0137] The heat transfer efficiency η value is brought into the formula (36) to calculate the temperature of the oil after the heat transfer through the heat dissipation component, and the new oil supply temperature T is obtained again 滑出 . The oil supply temperature is compared with the previous assumed value. If they are equal, the iteration is ended. If they are not equal, the assumed value is corrected and the iteration is restarted. The calculation process of the thermal system is shown in Figure 6 .

[0138] Step five, modeling of the whole system.

[0139] The whole oil system is based on the subsystem models established in steps one, two, three, and four, and the data interaction between the subsystems: the calculation of the oil supply system depends on the front bearing cavity pressure P d1 , the middle bearing cavity pressure P d2 , the rear bearing cavity pressure P d3 , and the gear box pressure P d4 , the calculation of the oil return system and the thermal system depends on the oil supply pump outlet pressure P pump_out , the total oil supply amount Q d_all , the front bearing cavity nozzle flow Q d1 , the middle bearing cavity nozzle flow Q d2 , the rear bearing cavity nozzle flow Q d3 , and the gear box nozzle flow Q d4 calculated by the oil supply system, and the oil supply temperature T 滑出 , the oil return temperature T 回油 calculated by the thermal system affect the oil density ρ and the oil viscosity μ of the oil supply and the oil return, forming a whole system model calculation integrated with the oil supply system and the oil return system. The data interaction relationship is shown in Figure 7 .

[0140] The input parameters of the whole system model are mainly related to the engine operating conditions, the front pressure of the labyrinth seal , the rear pressure of the labyrinth seal , and the temperature T1 * before the labyrinth seal, the high-pressure rotor speed N2, the low-pressure rotor speed N3, and the flight height H fly , wherein the labyrinth seal structure parameters include the number of teeth N, the tooth tip thickness t, the seal gap c, the flow area A, the front pressure of the labyrinth seal , the rear pressure of the labyrinth seal , and the temperature T1 * before the labyrinth seal. The temperature is calculated by the ventilation model to obtain the front bearing cavity pressure P d1 , the middle bearing cavity pressure P d2 , the rear bearing cavity pressure P d3 , the gear box pressure P d4 , and the oil tank pressure P tank, high-pressure rotor speed N2, radiator inlet fuel flow W and radiator inlet fuel temperature T 滑入 The oil supply temperature T is calculated through a thermodynamic model 滑出 , and the oil return temperature T 回油 The supply / return oil flow, the oil supply pressure, and the supply / return oil temperature parameters at each oil circuit of the system are obtained by inputting the two output parameters into the oil circuit system model formulas (3) and (20). The calculation process of the oil supply system model is shown in Figure 8 .

[0141] Step six, the common faults of the oil system are simulated and simulated.

[0142] The fault model considers the whole system model, the mechanism of the oil system fault, the change rule of the characteristic parameters of the pump, the oil filter, the radiator conduit component when the fault occurs, and the change rule of the measurement point parameters, and seven types of pump shaft fracture, oil-gas separator damage, oil supply filter blockage, servo fuel heater fuel leakage, fuel-oil radiator oil pipeline blockage, fuel-oil radiator fuel leakage and main oil return filter blockage are obtained, and eight characteristic parameters η v , oil tank level h, oil filter flow resistance Δp b , main oil flow Q all_回油 , heat exchange efficiency η, engine heat generation H, oil circuit flow resistance Δp c2 , oil filter flow resistance Δp f are adjusted and set, and the measurement point parameter values are simulated and calculated. The specific simulation adjustment setting mode of each type of fault is shown in Table 1.

[0143] Table 1 Fault characteristic parameters and adjustment setting mode

[0144]

[0145]

[0146] Finally, the parameter values calculated by simulation and simulation can reproduce the performance parameter changes and measurement point signal changes of the corresponding components when the pump shaft fracture, oil-gas separation mechanism damage, oil supply filter blockage, oil return filter blockage, servo fuel heater fuel leakage, fuel-oil radiator fuel leakage, and fuel-oil radiator blockage occur. The fault model is established, and the fault simulation of the oil system is completed.

[0147] Advantages

[0148] The modeling and fault simulation method for the oil system of an aero-engine provided by the application has the following effects:

[0149] 1. The component, subsystem model of the aero-engine lubricating oil system is established in turn, and the lubricating oil system model based on Matlab / Simulink is established through coordinating the interaction of each subsystem model, and the Matlab / Simulink model applicable to the onboard calculation is obtained.

[0150] 2. The problems such as difficulty in cooperative simulation, inconvenience in data interaction between subsystems, and low calculation efficiency of the model established by the professional software such as Flowmaster are avoided.

[0151] 3. The lubricating oil system fault simulation function is realized by analyzing the system parameter change caused by the fault, and the test platform of the aero-engine lubricating oil system fault diagnosis algorithm is provided, and the change of the component performance parameter under each fault state can be analyzed and calculated very conveniently and efficiently. BRIEF DESCRIPTION OF DRAWINGS

[0152] The accompanying drawings are included to provide a further understanding of the application, and are incorporated herein and constitute a part of the detailed description. The same reference numbers in the drawings indicate the same elements.

[0153] Figure 1 The calculation flow chart of the oil supply system;

[0154] Figure 2 The calculation flow chart of the oil return pump working condition;

[0155] Figure 3 The calculation flow chart of the oil return pressure;

[0156] Figure 4 The calculation flow chart of the mid-bearing cavity pressure;

[0157] Figure 5 The calculation flow chart of the ventilation system;

[0158] Figure 6 The iterative calculation flow chart of the thermal system;

[0159] Figure 7 The data interaction relationship diagram between the subsystems;

[0160] Figure 8 The calculation flow chart of the lubricating oil system model;

[0161] Figure 9 The relative error of the calculation results of the Simulink model and the Flowmaster model under the standard take-off. DETAILED DESCRIPTION

[0162] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0163] This invention provides a modeling and fault simulation method for aero-engine lubricating oil systems, the specific steps of which are as follows:

[0164] Step 1: Modeling the oil supply subsystem.

[0165] The first step is component modeling, and the second step is subsystem iterative algorithm calculation and fuel supply system modeling.

[0166] For component 1 of the oil supply system, the oil pump, the theoretical formula for calculating the pump flow rate is:

[0167] Q p理论 =N p ·V=N2i·V(1)

[0168] In the formula N p N1 and N2 are the pump speed and high-pressure rotor speed, respectively, in rpm. i is the transmission ratio between the engine high-pressure shaft and the fuel pump shaft, i.e., N p = N2·i, where V is the pump displacement. The actual flow rate of the oil supply pump is also affected by the volumetric efficiency η. v Impact:

[0169] Q p实际 =Q p理论 η v (2)

[0170] Substituting the existing pump speed and flow rate test data into equations (1) and (2), the pump volumetric efficiencies at speeds of 3000, 4200, and 6250 rpm are 0.98, 0.96, and 0.92, respectively. Fitting was performed using the cftool fitting toolbox in MATLAB. Since the volumetric efficiency changes monotonically within the given speed range and there are only 3 data points, a second-order fitting was used. The fitting results are as follows:

[0171]

[0172] The sum of squared errors between the fitted curve and the data points is 1.233 × 10⁻⁶. -32 After linear fitting:

[0173] η v = -1.857 × 10 -5 N p +1.037

[0174] The SSE (sum of square error) of the volumetric efficiency fitting curve and the data points is 3.024 x 10 -6 The fitting effect is good, and the rotating speed in the test data basically covers the rotating speed of the pump under the common working condition, so the formula (2) can better reflect the change of the pump volumetric efficiency when the oil system works.

[0175] Based on the above, the model of the oil supply pump flow is:

[0176]

[0177] For the oil supply pipeline model of the oil supply system component 2, the oil supply pipeline resistance Δp a is calculated by the following formula:

[0178]

[0179] In the formula, L a is the pipe length, d a is the oil supply pipeline inner diameter, v a is the flow rate, ρ is the oil density, f a is the friction coefficient, and for viscous liquids such as oil, it is calculated according to the formula The Reynolds number Re is calculated by the following formula

[0180]

[0181] In the formula, v a is the flow rate, d a is the inner diameter, ρ and μ are the oil density and kinematic viscosity. For the relationship between the kinematic viscosity of the 4050 oil and the temperature t, take A = 0.6, B = 21.520, and C = 3.540, that is, μ = exp[exp(21.52 + 3.54ln(t + 273))] - 0.6

[0182] For the oil supply filter model of the oil supply system component 3, the oil filter resistance Δp b is calculated by the following formula:

[0183] Δp b = Δp b1 + Δp b2 = K'ξ11V b 2 ρ / 2+ξ2V b 2 ρ / 2 (5)

[0184] In the formula, Δp b1 is the filter resistance, Δp b2 is the shell inlet resistance loss, K' is the Reynolds number influence correction coefficient; V bWhere, Q is the flow rate of the oil, L / min, A is the filter screen area, m2, ξ1 is the filter core resistance coefficient, ξ2 is the local resistance coefficient at the shell inlet, and ρ is the oil density.

[0185] The oil filter resistance characteristics are obtained by using the test data fitting method, so the relationship between the flow resistance and the flow rate needs to be determined first, and the formula is:

[0186]

[0187] Where, ξ = K'ξ1 + ξ2, Q b is the flow rate of the oil, L / min, A b is the filter screen area, m2. 2

[0188] The oil filter resistance characteristic calculation formula is set as:

[0189] Δp b = k b Q b 2 (Pa) (7)

[0190] Where, Q is the flow rate of the oil, L / min, k is the oil filter resistance characteristic coefficient, and the oil filter resistance characteristic test data are known. The relationship between the flow resistance loss and the oil flow rate is fitted according to the test data using the Polynomial polynomial fitting function of the cftool toolbox in MATLAB, and the fitting result is k b = 33.85.

[0191] The oil filter has a differential pressure switch quantity sensor, and when the differential pressure of the oil filter is too large, the differential pressure switch quantity changes, which is used to indicate that the oil filter is blocked. The threshold value is a known parameter, so the oil filter model needs to output the differential pressure switch quantity in addition to calculating the flow resistance. The differential pressure switch quantity "1" represents that the oil filter is blocked, and "0" represents that it is not blocked.

[0192] For the flow resistance model of the servo fuel heater and the fuel oil heat dissipation of the oil supply system component 4, the flow resistance characteristics of the two heat exchangers can be calculated in three parts, and the calculation formula is as follows:

[0193] ΔP s = ΔP0φd0 + ΔP ip + ΔP Ns (8)

[0194] Where, ΔP s is the heat dissipation pressure drop, ΔP0 is the tube bundle pressure drop, ΔP ip is the guide plate pressure drop, and ΔP Ns is the shell inlet nozzle pressure drop. The calculation method of each part of the pressure drop is shown in the following formula:

[0195] ​

[0196]

[0197]

[0198] wherein V0 is the mass flow rate of the shell side fluid, kg / (m 2 ·s); V Ns is the mass flow rate at the inlet and outlet of the shell side baffle, kg / (m 2 ·s); ξ0 is the friction resistance coefficient for circular pipe of the shell side fluid; φ0 is the viscosity correction coefficient of the shell side fluid; ρ s is the density of the shell side fluid, kg / m 3 ; D s is the inner diameter of the shell, m; n b is the number of baffles; d e is the equivalent diameter of the shell side, m; ξ ip is the resistance coefficient of the baffle.

[0199] Let the resistance characteristic Δp c1 of the servo fuel heater and the resistance characteristic Δp c2 of the fuel oil radiator be calculated as follows:

[0200] Δp c1 = k c1 Q c 2 (Pa) (12)

[0201] Δp c2 = k c2 Q c 2 (Pa) (13)

[0202] wherein Q c is the oil flow rate, unit L / min, k c1 is the servo fuel heater resistance characteristic coefficient, k c2 is the fuel oil radiator resistance characteristic coefficient. According to the known resistance characteristic test data, the relationship between flow resistance loss and oil flow rate is fitted using the Polynomial polynomial fitting function of the cftool toolbox in MATLAB, and the fitting results are k c1 = 27.8, k c2 = 28.2.

[0203] For the oil supply system component 5, the oil nozzle flow model is divided into a nozzle physical model and a nozzle iterative calculation module.

[0204] The oil nozzle flow calculation formula of the nozzle physical flow model is as follows:

[0205]

[0206] where Q d is the nozzle flow rate, in L / min; C d is the flow coefficient; d d is the nozzle diameter, in mm; Δp d is the difference between the nozzle front pressure and back pressure, in bar; and p is the lubricant density, in g / cm 3 .

[0207] For the nozzle iteration algorithm, the nozzle iteration algorithm module is the flow rate of the nozzle Q jet = f(P u , P b ), while P u differs from the pressure P0 at the pipeline node by a pipeline loss Δp pipe , and the pipeline loss is Δp pipe = f(Q pipe ) under the given pipeline property parameters, the pipeline flow rate and the nozzle flow rate should satisfy the conservation Q jet = Q pipe , otherwise, take Q pipe ' = (Q pipe + Q jet ) / 2, until the iteration calculation of the two differs by less than a threshold value. Taking the No. 1 bearing with the minimum oil supply as an example, the design value of the oil supply at this position is about 3 L / min, and the threshold value is set to ensure that the relative error of the nozzle flow rate after convergence and the accurate theoretical value is less than 0.33%, meeting the accuracy requirement.

[0208] For the bypass valve of the oil supply system component 6, the working state judgment model of the valve compares the total pressure drop with the opening pressure of the bypass valve to achieve the opening and closing of the bypass valve. If it is greater than, the bypass valve is opened, the valve opening identifier is set to 1, and the flow resistance is the valve opening pressure. If it is less than, the outlet pressure of the fuel lubricant radiator is taken as the outlet pressure of the valve, and the valve opening identifier is set to 0.

[0209] For the iteration module of the oil supply system, first, the high-pressure rotor speed N2 is obtained from the engine speed sensor, the pump outlet pressure P pump_out is set, and the pump flow rate Q

[0210] Secondly, the front bearing cavity pressure P d1 , the middle bearing cavity pressure P d2 , the rear bearing cavity pressure P d3 , and the gearbox pressure P d4 are input.And the oil supply system component 2 oil supply pipeline resistance Δp is calculated according to formula (3), (7), (12) and (13) a The oil system component 3 oil filter resistance Δp b The oil supply system component 4 servo fuel heater resistance characteristic Δp c1 And the fuel oil radiator resistance characteristic Δp c2 According to the oil supply system connection structure, the gear box nozzle front pressure P is calculated in turn u_4 That is

[0211] p u_4 =P0-ΔP a -Δp b -Δp c1 -Δp c2 (15)

[0212] Wherein, P0 is atmospheric pressure, ΔP a is the oil supply pipeline resistance, Δp b is the oil filter resistance, Δp c2 is the fuel oil radiator resistance characteristic, Δp c1 is the servo fuel heater resistance characteristic.

[0213] The rear bearing cavity nozzle front pressure P u_3 That is

[0214] P u_3 =P u_4 -ΔP a (16)

[0215] Wherein, P u_4 is the gear box nozzle front pressure, ΔP a is the oil supply pipeline resistance.

[0216] The middle bearing cavity nozzle front pressure P u_2 That is

[0217] P u_2 =P u_3 -ΔP a (17)

[0218] Wherein, P u_3 is the gear box nozzle front pressure, ΔP a is the oil supply pipeline resistance.

[0219] The front bearing cavity nozzle front pressure P u_1 That is

[0220] P u_1 =P u_2 -ΔP a (18)

[0221] Wherein, P u_2The front bearing cavity nozzle pressure ΔP a The oil supply pipeline resistance.

[0222] The front bearing cavity nozzle flow Q d1 , the middle bearing cavity nozzle flow Q d2 , the rear bearing cavity nozzle flow Q d3 and the gear box nozzle flow Q d4 are calculated in sequence by formula (14) and the nozzle iteration algorithm, and the total oil supply amount Q d_all of the nozzles is obtained.

[0223] Q d_all = Q d1 + Q d2 + Q d3 + Q d4 (19)

[0224] Wherein, Q d1 is the front bearing cavity nozzle flow, Q d2 is the middle bearing cavity nozzle flow, Q d3 is the rear bearing cavity nozzle flow, and Q d4 is the gear box nozzle flow.

[0225] Finally, the total oil supply amount Q d-all of the nozzles is compared with the pump flow to correct the pump rear pressure. When the total oil supply amount Q d-all of the nozzles is less than the pump flow , the oil supply pump rear outlet pressure P pump_out is increased, and vice versa. The iteration is repeated until the difference between them is within the allowable range. In the iteration algorithm, the Simulink module for updating the pump rear pressure compares the oil supply pump flow and the nozzle flow, takes the error threshold of the total nozzle flow and the oil supply pump flow as 0.1 L / min, corrects the pump rear pressure, and the oil supply amount of the lubricating oil system under normal working condition is 45-50 L / min.

[0226] The front bearing cavity, the middle bearing cavity, the rear bearing cavity, the gear box and the oil supply pump rear pressure under the most commonly used standard take-off working condition are compared with the output of the model built by using the commercial software Flowmaster. Under the standard take-off working condition and the same input condition, the comparison of the output results of the oil supply system Simulink model and the Flowmaster model shows that the relative error of the calculation result is kept within 5%, which meets the engineering precision requirement and verifies the effectiveness of the oil supply system Simulink model.

[0227] Step two, modeling of the oil return subsystem.

[0228] One is modeling of the component, and the other is modeling of the oil return system.

[0229] For the return oil pump model of component 1 of the return oil system, its working status is determined by the switch module. When the pump inlet pressure after calculating the pressure loss of gears or bearings is compared with the minimum allowable pressure by the switch module, if it is greater than the minimum allowable pressure, the pump will work normally and output the identifier "1"; otherwise, it will output "0".

[0230] For the return oil system component 2, the return oil pipeline model, similar to the supply oil pipeline, only its resistance characteristics are considered, not its heat transfer characteristics, and only the friction loss is calculated, not the local loss. The formula for calculating the pipeline flow resistance is:

[0231]

[0232] Where Δp e For two-phase flow pipeline losses, Δp g For losses in single-phase gas flow pipelines, This is a correction factor. The calculation method varies with the state of the two-phase flow. Generally, the return flow of lubricating oil is in the form of bubble flow, and the calculation formula is:

[0233]

[0234] in ρ L ρ g Densities of the liquid and gas phases (kg / m³) 3 );W L W G The mass flow rates (kg / h) of the liquid and gas phases are given by ρ. L ρ g Based on the oil supply volume calculated by the oil supply system and the set oil-air ratio, the corresponding mass flow rate can be calculated.

[0235] The modeling method for component 3 of the return oil system, the return oil filter, is the same as that for the supply oil filter, considering only its resistance characteristics. Since the resistance characteristics are proportional to the square of the flow rate, it is necessary to refit the data based on the flow resistance characteristics test data. The formula for calculating the relationship between the return oil filter flow resistance and the return oil flow rate is assumed to be:

[0236] Δp f =k3Q f 2 (twenty one)

[0237] In the formula Q f Let k be the return oil flow rate in L / min, and k3 be the resistance characteristic coefficient of the return oil filter. Based on the known test data of the return oil filter resistance characteristics, the Polynomial function of the cftool toolbox in MATLAB was used to fit the relationship between flow resistance loss and lubricating oil flow rate, and k3 = 15.20 was obtained.

[0238] There is a differential pressure switch sensor at the return oil filter to indicate oil filter blockage. When the differential pressure of the return oil filter exceeds a certain threshold, the differential pressure switch value changes. The threshold is a known parameter, so the return oil filter model outputs a differential pressure switch value. A switch value of "1" represents oil filter blockage, and "0" represents no blockage. Its working status is determined through the switch module.

[0239] For the oil level model of component 4, the lubricating oil tank, in the oil return system, given the initial lubricating oil volume of 15L, and assuming the oil tank is a horizontally placed cuboid with dimensions of 530mm x 240mm x 50mm and a base area of ​​0.1272m³, the oil level height within the tank can be calculated using the formula for the volume of a cuboid. The calculated oil level under normal operating conditions is 77.26mm. The formula for calculating the volume V of the pipeline cylinder is also provided.

[0240] V=S×h (22)

[0241] Where S is the area of ​​the liquid bottom surface and h is the liquid level height or length.

[0242] The volume of each section of the oil supply and return system can be calculated sequentially. The sum of the volumes of each section of the pipeline is the amount of lubricating oil contained in the oil supply system pipeline. After obtaining the amount of lubricating oil contained in the oil supply and return pipelines and each component, the amount of lubricating oil in the oil tank can be calculated. Given that the oil tank is a cuboid, the oil level in the tank can be calculated according to the cuboid volume formula (22).

[0243] For the establishment of the iterative algorithm module for the oil return system, firstly, the oil tank pressure P is set. tank0 The nozzle flow rate Q in the front bearing cavity obtained in step one d1 Flow rate Q of nozzle in bearing cavity d2 , Rear bearing cavity nozzle flow rate Q d3 and gearbox nozzle flow rate Q d4 Oil supply Q to the front bearing cavity 前 Oil supply Q to the bearing cavity 中 Rear bearing cavity oil supply Q 后 and gearbox oil supply Q 齿 Therefore, the oil supply to each component is multiplied by the oil-air ratio γ. g Right now

[0244] Q′=Q×γ g (twenty three)

[0245] Where Q′ is the flow rate through each bearing, Q is the oil supply to each bearing, and γ g This refers to the oil-to-gas ratio.

[0246] Calculate the flow rates through the front bearing cavity, middle bearing cavity, rear bearing cavity, and gearbox using Q.all_回油 =Q 前′ +Q 中′ +Q 后′ +Q 齿′ The sum of the flow rates is the main loop flow rate Q. all_回油 .

[0247] Secondly, assuming the starting pressure P of the main return oil circuit 主回路 Starting from the main return oil line, the pressure loss Δp of the return oil pipeline of component 2 of the return oil system is calculated sequentially according to formulas (20) and (21). e Pressure loss Δp of component 3 return oil filter f Component 4, oil tank pressure P tank Right now

[0248] P tank =P 主回路 -Δp e -Δp f (twenty four)

[0249] Among them, P 主回路 Main return oil circuit starting pressure, Δp e For the pressure loss in the return oil pipeline, Δp f This is the pressure loss from the return oil filter.

[0250] Finally, compare the calculated pressure P of the lubricating oil tank. tank With the set oil tank pressure P tank0 If the difference is greater than the threshold, then the outlet pressure P after the return oil pump is corrected. 回油′ If the output pressure is less than the given value, the iteration stops and the main return oil pressure P is output. 主回路 .

[0251] In this example, the threshold is set at 500Pa, and the design value of the lubricating oil tank pressure under cruise conditions is about 50KPa, which can ensure that the relative error between the return oil outlet pressure and the lubricating oil tank pressure is less than 1.5%.

[0252] Step 3: Modeling the ventilation system.

[0253] It is mainly divided into two parts: the modeling of components and the design of iterative algorithms for subsystems and the modeling of ventilation systems.

[0254] For the sealing grate model of ventilation system component 1, the sealing leakage is calculated based on the sealing gas pressure, temperature, and bearing cavity pressure. The formula for calculating the sealing gas leakage of the grate is as follows:

[0255]

[0256] In the formula The leakage mass flow rate is kg / s; A1 is the flow area, m². 2 T1 *P0is the gas temperature before the labyrinth, Pa; P0is the leakage coefficient, and its calculation formula is:

[0257]

[0258] Where t is the tooth tip thickness, m; c is the sealing gap, m; N is the number of teeth; P0is the pressure before the labyrinth, Pa; P0is the pressure after the labyrinth, Pa; k, a are empirical coefficients.

[0259] The calculation formula of the ventilation system component 2 ventilation pipeline resistance characteristic Δp h is as follows:

[0260]

[0261] Where L h is the ventilation pipeline length, m; d h is the ventilation pipeline inner diameter, m; v h is the ventilation pipeline flow rate, m / s; ρ0is the air density, kg / m 3 ; f h is the friction coefficient, which is affected by the flow and the pipeline material, and is calculated according to the Reynolds number Re h , and the calculation method is:

[0262]

[0263] The air density ρ0is obtained according to the ideal gas state equation

[0264]

[0265] Where is the atmospheric pressure, V0is the ideal gas volume, n represents the amount of gas substance, t0=-0.0059H fly +18 is the gas Celsius temperature, R is the ideal gas constant 8.314 J / (mol·K), and M is the air molar mass, g / mol.

[0266] For the ventilation system component 3, the fitting of the axial ventilator obtains the resistance characteristic Δp i model, as shown below:

[0267] Δp i =0.0148N3+579.1Q a -44.5(kPa)(28)

[0268] Where N3is the low-pressure rotor speed, rpm; Q a is the ventilation gas mass flow, g / s.

[0269] The leakage amount of the screen is calculated as mass flow rate, while the flow resistance of the ventilation pipeline is calculated as volume flow rate. Therefore, a conversion module is needed to connect the screen model and the ventilation pipeline. The calculation formula of the conversion module is as follows:

[0270]

[0271] In the above formula, is the volume flow rate (L / min), is the mass flow rate (kg / s), and p is the gas density (kg / m 3 ).

[0272] For the iterative algorithm design of the ventilation system, the ventilation system model is a flow-pressure model. The iterative calculation in the model establishment can be divided into two parts: the pressure of the middle and rear bearing cavities and the pressure of each bearing cavity.

[0273] First, the pressure of the middle and rear bearing cavities is calculated. The iterative principle of the middle cavity pressure is pressure balance. First, input the temperature T1 * before the screen sealing, the pressure before the screen sealing, the number of screen teeth N, the sealing gap c, the flow area A, the tooth tip thickness t, and the set middle bearing cavity pressure value P 中 . Calculate the screen sealing gas leakage amount of the ventilation system component 1 according to formula (25) and formula (26) Second, calculate the ventilation flow resistance Δp h from the middle bearing cavity to the front bearing cavity according to formula (27) d2 . Then, the middle bearing cavity pressure P d2 is obtained as follows:

[0274] P d1 = P h + Δp d1 (30)

[0275] where P h is the front bearing cavity pressure, and Δp d2 is the ventilation flow resistance from the middle bearing cavity to the front bearing cavity.

[0276] Finally, compare the middle bearing cavity pressure P d2 with the set middle bearing cavity pressure value P d2 . If the difference is greater than a threshold value, correct the middle bearing cavity pressure P d2 . If the difference is less than the threshold value, stop the iteration and output the middle bearing cavity pressure P * . The calculation process is shown in Figure 4 .

[0277] Second, calculate the pressure in each bearing cavity. First, input the temperature T1 of each bearing cavity before the teeth are sealed. * Pressure before sealing the teeth Pressure after the fangs are sealed The parameters are: number of teeth N, sealing clearance c, flow area A, tooth tip thickness t, and pre-set bearing cavity pressure P. d1_0 , middle bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 and gearbox pressure P d4_0 According to formulas (25) and (26), the gas leakage of the ventilation system component 1 sealing the grate of each bearing cavity is calculated respectively. Secondly, the ventilation resistance Δp from the middle bearing cavity to the front bearing cavity is calculated according to formula (27). h The ventilation flow resistance Δp between the rear bearing cavity and the front bearing cavity h The ventilation flow resistance Δp from the gearbox to the front bearing cavity h ", from the obtained bearing cavity pressure P d2 Rear bearing cavity pressure P d3 and gearbox pressure P d4

[0278] P d2 =P1+Δp h P d3 =P1+Δp h ′,P d4 =P1+Δp h " (31)

[0279] Where P1 is the pressure in the front bearing cavity, Δp h The ventilation flow resistance from the middle bearing cavity to the front bearing cavity is Δp. h ′ represents the ventilation flow resistance from the rear bearing cavity to the front bearing cavity, Δp h "This refers to the ventilation flow resistance from the gearbox to the front bearing cavity."

[0280] Based on formulas (28) and (29), the resistance characteristic Δp of the 3-axis ventilator in the ventilation system is obtained. i The pressure P in the front bearing cavity d1 Calculation

[0281] P d1 =P0+Δp i (32)

[0282] Among them, P d1 The pressure in the front bearing cavity is P0 (atmospheric pressure) and Δp. i This refers to the resistance characteristics of the axial ventilator.

[0283] Finally, compare the bearing cavity pressure P before the pressure in each bearing cavity. d1Front bearing cavity pressure P d2 Rear bearing cavity pressure P d3 Gearbox pressure P d4 Set front bearing cavity pressure P d1_0 Front bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 Gearbox pressure P d4_0 If the difference is greater than a threshold, correct the set front bearing cavity pressure P d1_0 Front bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 Gearbox pressure P d4_0 If less, stop iteration and output front bearing cavity pressure P d1 Front bearing cavity pressure P d2 Rear bearing cavity pressure P d3 Gearbox pressure P d4 .

[0284] The verification method of the effectiveness of the ventilation system model is to compare the output results of the corresponding Flowmaster model under the same input conditions. Under the standard take-off operating condition and the same input conditions, the comparison of the output results of the ventilation system Simulink model and the Flowmaster model shows that the relative error of the calculation results is kept within 1.5%, which meets the engineering precision requirements and verifies the effectiveness of the ventilation system Simulink model.

[0285] Step four, modeling of the thermal system.

[0286] The work mainly includes two parts: modeling of typical components and design of the iterative algorithm of the thermal system and modeling of the oil supply system.

[0287] For the thermal system component 1, the heat generation of the bearings and gears is obtained through linear interpolation of the test data, and the obtained calculation formula is as follows:

[0288] Heat generation of No. 1 bearing: H1 = 0.0006217N2-5.4 (Kw) (33-1)

[0289] Heat generation of No. 2 bearing: H2 = 0.00122N2-16.23 (Kw) (33-2)

[0290] Heat generation of No. 3 bearing: H3 = 0.003918N2-50.23 (Kw) (33-3)

[0291] Heat generation of No. 4 bearing: H4 = 0.0007466N2-8.74 (Kw) (33-4)

[0292] Heat generation of No. 5 bearing: H5 = 0.0001818N2-1.706 (Kw) (33-5)

[0293] Heat generated by the accessory gear box: H7 = 0.001204 N2-8.276 (Kw) (33-7)

[0294] Heat generated by the accessory gear box: H7 = 0.001204 N2-8.276 (Kw) (33-7)

[0295] Heat generated by the central transmission: H8 = 0.0008085 N2-7.153 (Kw) (33-8)

[0296] In the above formula, N2 is the high-pressure rotor speed, in rpm; H is the heat generated by the corresponding component, in Kw.

[0297] After obtaining the heat generated, the temperature rise ΔT of the oil flowing through the engine can be calculated according to the formula:

[0298]

[0299] In the formula, H is the heat generated by the engine, in KJ, i.e., the sum of the heat generated by all bearings and gears; C p is the specific heat capacity of the oil, which is 2.34 KJ / Kg·K; m is the mass of the oil, in kg.

[0300] For the thermal system component 2, the oil tank exchanges heat with the external environment, the oil exchanges heat with the tank in the form of heat conduction, and then the tank exchanges heat with the external environment in the form of convection. The heat transfer calculation formula of the entire heat exchange process is as follows:

[0301]

[0302] In the formula, h1 is the thermal conductivity of air, δ is the tank wall thickness; t1 is the local atmospheric temperature, which is calculated according to the atmospheric temperature with height change data table in the literature; t2 is the inner wall temperature of the oil tank, A' is the heat transfer area, which is equal to the surface area of the oil tank in this case, and λ is the tank thermal conductivity.

[0303] For the thermal system component 3, the servo fuel heater and the fuel oil radiator, the heat exchange efficiency definition formula in the related test is as follows:

[0304]

[0305] In the formula, η is the heat exchange efficiency, T 滑入 is the inlet oil temperature of the radiator, T 燃入 is the inlet fuel temperature of the radiator, T 滑出 is the outlet oil temperature of the radiator.

[0306] The heat exchange efficiency η is obtained by interpolation of the heat exchange characteristic test data of the tube-shell servo fuel heater and the fuel-oil radiator. The modeling of the fuel-oil radiator and the servo fuel heater is illustrated by taking the fuel-oil radiator as an example. The heat exchange efficiency of the fuel-oil radiator is obtained by fitting the test data of the radiator. One group of test conditions is fuel temperature of 57℃, and the other group is 71℃. Both groups are tested under fuel flow rates of 15, 20, 25, 30, and 35 L / min, a total of 10 conditions. The calculation formula under the 10 conditions obtained by fitting is as follows:

[0307] Fuel temperature 57℃, fuel flow rate 15 L / min:

[0308] Fuel temperature 57℃, fuel flow rate 20 L / min:

[0309] Fuel temperature 57℃, fuel flow rate 25 L / min:

[0310] Fuel temperature 57℃, fuel flow rate 30 L / min:

[0311] Fuel temperature 57℃, fuel flow rate 35 L / min:

[0312] Fuel temperature 71℃, fuel flow rate 15 L / min:

[0313] Fuel temperature 71℃, fuel flow rate 20 L / min:

[0314] Fuel temperature 71℃, fuel flow rate 25 L / min:

[0315] Fuel temperature 71℃, fuel flow rate 30 L / min:

[0316] Fuel temperature 71℃, fuel flow rate 35 L / min:

[0317] where y is the heat exchange efficiency η, and x is the fuel flow rate in L / min.

[0318] It can be seen from the fitting results that the calculation results of the fuel-oil radiator heat exchange characteristic model are good, with an absolute error of not more than 0.015 and a relative error of not more than 3.5%, verifying the effectiveness of the heat exchange efficiency calculation formula.

[0319] For the iterative algorithm modeling of the thermal system, a fuel supply temperature T滑出 , given engine operating parameters are high pressure rotor speed N2, by formula (33) to calculate the front bearing cavity 3 bearing heat H1, H2, H3, the middle bearing cavity heat H4, the rear bearing cavity heat H5, 3 gear box heat H6, H7, H8, the sum of the heat generated by the flow through the bearing and gear is the engine heat H. Combined with the source of the oil return system to get the front bearing cavity flow Q 前 , middle bearing cavity flow Q 中 , rear bearing cavity flow Q 后 and gear box flow Q 齿 , and by formula (34) to calculate its flow through the engine temperature rise ΔT and then by formula to get the oil return temperature T 回油 .

[0320] T 回油 = T 滑出 + ΔT (37)

[0321] Then according to formula (35) to calculate its heat dissipation φ in the oil tank, combined with the radiator inlet fuel flow W, radiator outlet oil temperature T 滑出 , the calculation can be obtained in the heat dissipation q

[0322] q = WC P (T 滑入 -T 滑出 ) (38)

[0323] Where, W is the radiator inlet fuel flow, C P is the specific heat capacity of the oil, the radiator inlet fuel temperature T 滑入 , T 滑出 is the radiator outlet oil temperature.

[0324] From the radiator heat transfer characteristic test data interpolation heat transfer efficiency η value into by formula (36) to calculate the temperature of the oil through the heat dissipation components, re get new oil supply temperature T 滑出 , the supply temperature and the previous assumption value comparison, if equal then iteration ends, not equal to correct the assumption value re iteration.

[0325] In the standard take-off conditions, the same input conditions, the output results of the thermodynamic system Simulink model and Flowmaster model can be obtained, the relative error of the calculation results is kept within 3.5%, meet the engineering precision requirements, verify the effectiveness of the thermodynamic system Simulink model.

[0326] Step five, the modeling of the whole system.

[0327] The full system modeling of the lubricating oil system is based on the models of the first step, the second step, the third step and the fourth step. The two parameters related to the engine working condition are inputted.

[0328] Firstly, the front pressure of the labyrinth seal the rear pressure of the labyrinth seal and the temperature T1 before the labyrinth seal * , the high-pressure rotor speed N2, the low-pressure rotor speed N3 and the flight height H fly The sealing structure parameters including the number of teeth N, the tooth tip thickness t, the sealing gap c and the flow area A are calculated through the ventilation system model to obtain the front bearing cavity pressure P d1 , the middle bearing cavity pressure P d2 , the rear bearing cavity pressure P d3 , the gear box pressure P d4 and the oil tank pressure P obtained by the oil return model. tank

[0329] Secondly, the high-pressure rotor speed N2, the radiator inlet fuel flow W and the radiator inlet fuel temperature T 滑入 The oil supply temperature T 滑出 and the oil return temperature T 回油 are calculated through the thermal system model, and then the supply / return oil flow, the oil supply pressure and the supply / return oil temperature parameters at each oil path of the system are obtained by inputting the two output parameters into the formulas (3) and (20) of the oil path system model. The output parameters of the full system basically cover all the main parameters reflecting the working condition of the lubricating oil system, including the front, middle and rear bearing cavity and gear box oil supply, oil supply temperature, oil supply pressure, main oil return temperature, front, middle and rear bearing cavity and gear box return temperature. The Simulink model of the lubricating oil system realizes the cooperation of each subsystem working model.

[0330] The comparison between the Simulink model output results and the Flowmaster calculation results under the standard take-off working condition and the fault-free condition is shown in the following table:

[0331] Table 2 Comparison of various data under the standard take-off working condition

[0332]

[0333]

[0334] The relative errors of the Simulink model and the Flowmaster model calculation under the standard take-off working condition and the fault-free condition are shown in the following table: Figure 9 Except for the relative errors of the main oil return temperature and the oil supply pump rear pressure being-6.77% and 5.45%, respectively, the relative errors of the remaining main output parameters are all kept within 5%, which verifies the effectiveness of the built Simulink model of the lubricating oil system.​

[0335] Step six, the common fault of lubricating oil system is simulated. The fault model considers the whole system model, the mechanism of the fault of lubricating oil system, the change rule of the characteristic parameters of pump, oil filter, radiator pipe component when the fault occurs, and the change rule of the parameters of measuring point. Seven types of faults are obtained, including pump shaft fracture, oil-gas separator damage, oil supply filter blockage, servo fuel heater fuel leakage, fuel and lubricating oil radiator lubricating oil pipeline blockage, fuel and lubricating oil radiator fuel leakage and main oil return filter blockage. Eight characteristic parameters η v , h, Δp b , Q all , η, H, Δp 回油 , Δp c2 , Δp f of the oil filter are adjusted and set, and the parameter values of the measuring point are simulated and calculated. The specific simulation adjustment and setting mode of each type of fault is shown in Table 2.

[0336] Finally, the parameter values simulated and calculated by MATLAB can realize the change of the performance parameters of the corresponding components and the change of the measuring point signals when the seven types of faults occur, including pump shaft fracture, oil-gas separator damage, oil supply filter blockage, oil return filter blockage, servo fuel heater fuel leakage, fuel and lubricating oil radiator fuel leakage, and fuel and lubricating oil radiator blockage. The fault model is established, and the fault simulation of the lubricating oil system is completed. For example, under the maximum cruising condition, the injection of the seven types of faults can obtain the measuring point parameter change results of the oil supply pressure and the oil level of the oil tank corresponding to the seven types of faults, as shown in Table 3.

[0337] Table 3 Fault measuring point parameter calculation results

[0338]

[0339] Therefore, the specific fault events obtained by other fault diagnosis methods can be achieved, for example, when the measuring point parameter data of the oil supply filter pressure difference changes, the fault simulation model can directly obtain that the oil supply filter of the lubricating oil system is blocked. Therefore, the modeling and fault simulation method of the aero-engine lubricating oil system also provides an accurate and reliable numerical simulation model of the lubricating oil system and fault simulation analysis results for the model establishment of the engine health information and engine health management system in the later period, and provides a test platform for the optimization design and health management of the lubricating oil system.

[0340] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A modeling method for aero-engine lubrication systems, characterized in that... The steps are as follows: Step 1: Modeling the oil supply subsystem; For component 1 of the oil supply system, the oil pump, the theoretical formula for calculating the pump flow rate is: Q p理论 =N p ·V=N2i·V (1) In the formula N p N1 and N2 represent the pump speed and high-pressure rotor speed, respectively, and i is the transmission ratio between the engine high-pressure shaft and the fuel pump shaft, i.e., N0. p =N2·i, where V is the pump displacement; the actual flow rate of the oil supply pump is also affected by the volumetric efficiency η. v Impact: Q p实际 =Q p理论 the v (2) For the oil supply system component 2, the oil supply pipeline model, the oil supply pipeline resistance Δp a The calculation formula is as follows: In the formula L a For pipe length, d a v is the inner diameter of the pipe. a Let ρ be the flow velocity. oil f is the density of the lubricating oil. a The coefficient of friction is given by [formula], which is used for viscous liquids such as lubricating oil. The Reynolds number Re of the lubricating oil in the oil supply line is calculated as follows: In the formula, μ is the kinematic viscosity of the lubricating oil; For the oil supply system component 3, the oil filter model, the oil filter resistance Δp b The theoretical calculation formula is shown below: Δp b =Δp b1 +Δp b2 =K′ξ1V b 2 r oil / 2+ξ2V b 2 r oil / 2 (5) In the formula Δp b1 For filter element resistance, Δp b2 V represents the inlet drag loss of the casing, K′ is the correction factor for the Reynolds number effect; b ξ1 is the fluid velocity over the entire area of ​​the mesh, ξ2 is the filter element resistance coefficient, and ξ2 is the local resistance coefficient at the inlet of the shell. The oil filter resistance characteristics are obtained by fitting experimental data, so it is necessary to first determine the relationship between flow resistance and flow rate, as shown in the following formula: In the formula, ξ=K′ξ1+ξ2, Q b For lubricating oil flow rate, A b This refers to the cross-sectional area of ​​the oil filter screen. Let the formula for calculating the oil supply filter resistance characteristic be: In the formula k b This refers to the oil filter resistance characteristic coefficient. There is a differential pressure switch sensor at the oil supply filter. When the differential pressure of the oil supply filter is too large, the differential pressure switch changes to indicate that the oil filter is blocked. The threshold is a known parameter. Therefore, in addition to calculating the flow resistance, the oil supply filter model also needs to output the differential pressure switch. The differential pressure switch "1" represents that the oil filter is blocked and "0" represents that there is no blockage. For the flow resistance model of component 4 of the fuel supply system, the servo fuel heater and the lubricating oil heat exchanger, the calculation formulas for the flow resistance characteristics of these two heat exchangers are as follows: ΔP s =ΔP0φd0+ΔP ip +ΔP Ns (8) Where ΔP s ΔP0 is the voltage drop across the heatsink, ΔP0 is the voltage drop across the tube bundle, and ΔP0 is the voltage drop across the tube bundle. ip For the pressure drop across the guide vane, ΔP Ns The pressure drop at the shell-side inlet nozzle is given; the calculation method for the pressure drop of each part is shown in the following formula: In the formula, V0 is the shell-side fluid mass flow rate; V Ns ξ0 is the mass flow velocity at the inlet and outlet of the shell-side guide vane; φ0 is the frictional resistance coefficient of the shell-side fluid in the circular tube; φ0 is the viscosity correction coefficient of the shell-side fluid; ρ s D is the shell-side fluid density; s n is the inner diameter of the shell; b d is the number of baffles; e ξ is the shell-side equivalent diameter; ip The drag coefficient of the guide vane; Assume the resistance characteristic Δp of the servo fuel heater c1 Resistance characteristics Δp of fuel oil radiator c2 The calculation formula is: Δp c1 =k c1 Q c 2 (12) Δp c2 =k c2 Q c 2 (13) In the formula Q c k is the lubricating oil flow rate. c1 k is the resistance characteristic coefficient of the servo fuel heater. c2 The resistance characteristic coefficient of the lubricating oil radiator; The lubricating oil nozzle flow model for component 5 of the oil supply system is divided into a nozzle physical model and a nozzle iterative calculation module; the lubricating oil nozzle flow calculation formula of the nozzle flow physical model is shown below: In the formula Q d C is the nozzle flow rate; d d is the flow coefficient; d Δp is the nozzle orifice diameter. d This is the difference between the nozzle's front pressure and back pressure. The nozzle iterative algorithm module is established with the initial input setting of the nozzle inlet flow rate Q. a_0 Pressure P0 at the nozzle inlet node, lubricating oil density ρ oil And the lubricating oil viscosity μ, the nozzle flow rate is Q d =f(P u ,P b ), front pressure P u The pressure P0 at the pipeline node differs from the pipeline loss Δp. a That is, P u =Δp a +P0, while the pipeline loss is Δp given the pipeline physical parameters. a =f(Q) a The flow rate in the pipeline and the flow rate in the nozzle should satisfy the conservation condition Q. d =Q a Otherwise, the difference between the pipeline flow rate and the nozzle flow rate will be reduced by half (Q). a ′=(Q a +Q d The process continues until the difference between the two values ​​is less than a threshold. For the bypass valve of component 6 of the fuel supply system, the valve modeling is achieved by comparing the total pressure drop with the opening pressure of the bypass valve through the switch module to realize the opening and closing of the bypass valve; if it is greater, the bypass valve opens, the valve opening identifier is set to 1, and the flow resistance is the valve opening pressure; if it is less, the fuel lubricating oil radiator outlet pressure is used as the valve outlet pressure output, and the valve opening identifier is set to 0. For the establishment of the fuel supply system iterative module: First, the high-pressure rotor speed N2 is obtained from the engine speed sensor, and the outlet pressure P of the fuel supply pump is set. pump_out The pump flow rate is calculated using formula (2). Secondly, input the front bearing cavity pressure P d1 , middle bearing cavity pressure P d2 Rear bearing cavity pressure P d3 and gearbox pressure P d4 The resistance Δp of the oil supply pipeline of component 2 of the oil supply system is calculated according to formulas (3), (7), (12) and (13). a Oil system component 3 Oil filter resistance Δp b Resistance characteristics Δp of servo fuel heater in fuel supply system component 4 c1 Resistance characteristics Δp of fuel oil radiator c2 Based on the connection structure of the fuel supply system, the pre-pressure P of the gearbox nozzle is calculated sequentially. u_4 Right now P u_4 =P0-ΔP a -ΔP b -ΔP c1 -ΔP c2 (15) Where P0 is atmospheric pressure, ΔP a For the resistance of the oil supply line, Δp b For oil filter resistance, Δp c2 For the resistance characteristics of the lubricating oil radiator, Δp c1 The resistance characteristics of the servo fuel heater; Rear bearing cavity nozzle front pressure P u_3 Right now P u_3 =P u_4 -ΔP a (16) Among them, P u_4 For the gearbox nozzle pre-pressure, ΔP a For the resistance of the oil supply pipeline; The pressure P before the nozzle in the bearing cavity u_2 Right now P u_2 =P u_3 -ΔP a (17) Among them, P u_3 For the pre-pressure of the nozzle in the rear bearing cavity, ΔP a For the resistance of the oil supply pipeline; Front bearing cavity nozzle pre-pressure P u_1 Right now P u_1 =P u_2 -ΔP a (18) Among them, P u_2 For the nozzle front pressure in the bearing cavity, ΔP a For the resistance of the oil supply pipeline; The flow rates Q of the front bearing cavity nozzles at the four oil supply points of the oil supply system are calculated sequentially using formula (14) and the nozzle iteration algorithm. d1 Flow rate Q of nozzle in bearing cavity d2 , Rear bearing cavity nozzle flow rate Q d3 and gearbox nozzle flow rate Q d4 And obtain the total fuel supply Q of the nozzle. d_all Right now Q d_all =Q d1 +Q d2 +Q d3 +Q d4 (19) Among them, Q d1 Q is the nozzle flow rate in the front bearing cavity. d2 Q is the flow rate of the nozzle in the bearing cavity. d3 Q is the flow rate of the nozzle in the rear bearing cavity. d4 The flow rate of the nozzle in the gear bearing cavity; Finally, compare the total fuel supply Q from the nozzles. d-all With pump flow rate Q p实际 To correct the pump post-pump pressure, when the total fuel supply Q from the nozzles... d-all Less than pump flow rate At that time, the outlet pressure P after the oil supply pump is increased. pump_out If the difference is greater, then decrease it, and repeat the iteration until the difference between the two is within the allowable range; Step 2: Modeling the oil return subsystem For the return oil pump model of component 1 of the return oil system, the normal operation of the lubricating oil system requires that the pressure before the pump is greater than the minimum allowable pressure. When the pressure before the pump after calculating the pressure loss of the gear or bearing is compared with the minimum allowable pressure through the switch module, if it is greater than the minimum allowable pressure, the normal operation is output with the identifier "1", otherwise it is output with "0". For the return oil pipeline model of component 2 of the return oil system, the formula for calculating the pipeline flow resistance is: Where Δp e For two-phase flow pipeline losses, Δp g For losses in single-phase gas flow pipelines, This is a correction factor; The modeling method for component 3 of the return oil system, the return oil filter, is the same as that for the supply oil filter. The formula for calculating the relationship between the return oil filter flow resistance and the return oil flow rate is: Δp f =k3Q f 2 (21) In the formula Q f K is the return oil flow rate, and k3 is the resistance characteristic coefficient of the return oil filter. There is a differential pressure switch sensor at the return oil filter to indicate oil filter blockage. When the differential pressure of the return oil filter exceeds a certain threshold, the differential pressure switch value changes. The threshold value is a known parameter. Therefore, the return oil filter model outputs a differential pressure switch value. The switch value "1" represents oil filter blockage, and "0" represents no blockage. The selection is implemented through the switch module. For the oil level model of component 4, the lubricating oil tank, given the initial lubricating oil volume, the calculation formula is used based on the cylinder volume V of the pipeline. V=S×h (22) where S is the bottom surface area of ​​the liquid and h is the liquid level height or length; The volume of each section of the oil supply and return system can be calculated in sequence. The sum of the volumes of each section of the pipeline is the amount of lubricating oil contained in the oil supply system pipeline. After obtaining the amount of lubricating oil contained in the oil supply and return pipeline and each component, the amount of lubricating oil in the oil tank can be calculated. Given that the oil tank is a cuboid, the oil level in the tank can be calculated according to the cuboid volume formula (22). For the establishment of the iterative algorithm module for the oil return system, firstly, the oil tank pressure P is set. tank0 The nozzle flow rate Q in the front bearing cavity obtained in step 1 d1 Flow rate Q of nozzle in bearing cavity d2 , Rear bearing cavity nozzle flow rate Q d3 and gearbox nozzle flow rate Q d4 Oil supply Q to the front bearing cavity 前 Oil supply Q to the bearing cavity 中 Rear bearing cavity oil supply Q 后 and gearbox oil supply Q 齿 Therefore, the oil supply to each component is multiplied by the oil-air ratio γ. g Right now Where Q′ is the flow rate through each bearing, Q is the oil supply to each bearing, and γ g The oil-to-gas ratio; Calculate the flow rates through the front bearing cavity, middle bearing cavity, rear bearing cavity, and gearbox using Q. all_回油 =Q 前′ +Q 中′ +Q 后′ +Q 齿' The sum of the flow rates is the main loop flow rate Q. all_回油 ; Secondly, assuming the starting pressure P of the main return oil circuit 主回路 Starting from the main return oil line, the pressure loss Δp of the return oil pipeline of component 2 of the return oil system is calculated sequentially according to formulas (20) and (21). e Pressure loss Δp of component 3 return oil filter f Component 4, oil tank pressure P tank Right now P tank =P 主回路 -Δp e -Δp f (24) Among them, P 主回路 Main return oil circuit starting pressure, Δp e For the pressure loss in the return oil pipeline, Δp f This is the pressure loss from the return oil filter; Finally, compare the calculated pressure P of the lubricating oil tank. tank With the set oil tank pressure P tank0 If the difference is greater than the threshold, then the outlet pressure P after the return oil pump is corrected. 回油′ If the output pressure is less than the given value, the iteration stops and the main return oil pressure P is output. 主回路 ; Step 3: Modeling the ventilation system For the sealing grate model of ventilation system component 1, the sealing leakage is calculated based on the sealing gas pressure, temperature, and bearing cavity pressure. The formula for calculating the sealing gas leakage of the grate is as follows: In the formula To determine the leakage mass flow rate, A represents the flow area, and T1* represents the gas temperature before the grating teeth; The leakage coefficient is calculated using the following formula: In the formula, t is the tooth tip thickness, c is the sealing clearance, and N is the number of teeth; The pressure before the tooth is formed. The pressure after the tooth is given in Pa; k and a are empirical coefficients. For ventilation system component 2, the resistance characteristic Δp of the ventilation duct h The calculation formula is as follows: In the formula L h For the length of the ventilation duct, d h v is the inner diameter of the ventilation duct. h The velocity in the ventilation duct is ρ0, the air density is f. h The coefficient of friction is affected by both the fluid and the pipe material, based on the Reynolds number Re in the ventilation duct. h The calculation method is as follows: The air density ρ0 is obtained from the ideal gas law. In the formula Let V0 be the ideal gas volume, n be the amount of gas, and t0 = -0.0059H. fly +18 is the Celsius temperature of the gas, R is the ideal gas constant 8.314 J / (mol·K), and M is the molar mass of air; For ventilation system component 3, the resistance characteristic Δp is obtained by fitting the axial ventilator. i The model is as follows: Δp i =0.0148N3+579.1Q a -44.5(kPa) (28) In the formula, N3 is the low-pressure rotor speed, Q a This refers to the mass flow rate of the ventilation gas. The output of the grate leakage calculation is the mass flow rate, while the output of the ventilation duct flow resistance characteristic calculation is the volumetric flow rate. A conversion module for both flow rates is required to connect the grate sealing model and the ventilation duct. The calculation formula for the flow conversion module is shown below: In the above formula For volumetric flow rate, ρ gas The density of the gas; For the establishment of the ventilation system iterative module: First, for the design of the iterative algorithm for the ventilation system, the ventilation system model is a flow-pressure model. The iterative calculation in the model establishment can be divided into two parts: one is the pressure of the middle and rear bearing cavities, and the other is the pressure of each bearing cavity. First, consider the pressure in the middle and rear bearing cavities. Since the pressure calculations for the middle and rear bearing cavities are similar, we first build and connect the component models according to the physical structure of the middle and rear bearing cavities. The iterative principle for the pressure in the middle cavity is pressure balance. First, input the temperature T1* before the toothed teeth are sealed and the pressure before the toothed teeth are sealed. Pressure after the fangs are sealed The parameters are: number of teeth N, sealing clearance c, flow area A, tooth tip thickness t, and set bearing cavity pressure P. 中 The leakage mass flow rate of the ventilation system component 1 sealing grate seal is calculated according to formulas (25) and (26). Secondly, the ventilation resistance Δp from the middle bearing cavity to the front bearing cavity is calculated according to formula (27). h The pressure P in the bearing cavity is obtained from this. d2 Right now P d2 =P d1 +Δp h (30) Among them, P d1 The pressure in the front bearing cavity, Δp h This is the ventilation flow resistance from the middle bearing cavity to the front bearing cavity; Finally, compare the bearing cavity pressure P. d2 Compared with the set bearing cavity pressure value P d2 If the difference is greater than the threshold, then the bearing cavity pressure P is corrected. d2 If the output is less than the bearing cavity pressure P, then stop the iteration and output the bearing cavity pressure. d2 ; Second, calculate the pressure in each bearing cavity. First, input the temperature T1 of each bearing cavity before the teeth are sealed. * Pressure before sealing the teeth Pressure after the fangs are sealed The parameters are: number of teeth N, sealing clearance c, flow area A, tooth tip thickness t, and pre-set bearing cavity pressure P. d1_0 , middle bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 and gearbox pressure P d4_0 The mass flow rate of gas leakage from the sealing tooth of the ventilation system component 1 of each bearing cavity is calculated according to formulas (25) and (26). Secondly, the ventilation resistance Δp from the middle bearing cavity to the front bearing cavity is calculated according to formula (27). h The ventilation flow resistance Δp between the rear bearing cavity and the front bearing cavity h The ventilation flow resistance Δp from the gearbox to the front bearing cavity h ", from the obtained bearing cavity pressure P d2 Rear bearing cavity pressure P d3 and gearbox pressure P d4 : P d2 =P1+Δp h ,P d3 =P1+Δp h ′,P d4 =P1+Δp h ″ (31) Where P1 is the pressure in the front bearing cavity, Δp h The ventilation flow resistance from the middle bearing cavity to the front bearing cavity is Δp. h ′ represents the ventilation flow resistance from the rear bearing cavity to the front bearing cavity, Δp h "This refers to the ventilation resistance from the gearbox to the front bearing cavity; Based on formulas (28) and (29), the resistance characteristic Δp of the 3-axis ventilator in the ventilation system is obtained. i The pressure P in the front bearing cavity d1 Calculation P d1 =P0+Δp i (32) Among them, P d1 P0 is the pressure in the front bearing cavity, and Δp is the atmospheric pressure. i The resistance characteristics of the axial ventilator; Finally, compare the bearing cavity pressure P before the pressure in each bearing cavity. d1 , middle bearing cavity pressure P d2 Rear bearing cavity pressure P d3 and gearbox pressure P d4 With the set front bearing cavity pressure P d1_0 , middle bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 and gearbox pressure P d4_0 If the difference is greater than the threshold, then the pre-set bearing cavity pressure P is corrected. d1_0 , middle bearing cavity pressure P d2_0 Rear bearing cavity pressure P d3_0 and gearbox pressure P d4_0 If the value is less than the bearing cavity pressure P, then stop the iteration and output the bearing cavity pressure P. d1 , middle bearing cavity pressure P d2 Rear bearing cavity pressure P d3 and gearbox pressure P d4 ; Step 4: Modeling the thermal system For the bearings and gears of the thermal system component 1, the heat generated by the bearings and gears is obtained by linear interpolation of the experimental data, and the calculation formula is as follows: Heat generated by bearing number x: H=A·N2-B (33) In the above formula, N2 is the high-pressure rotor speed, H is the heat generated by the corresponding component; the values ​​of A and B are obtained by interpolation calculation. Once the heat generated is obtained, the temperature rise ΔT of the lubricating oil flowing through the engine can be calculated, according to the formula: In the formula, H represents the amount of lubricating oil heated by all bearings and gears in the engine, and C... p m is the specific heat capacity of the lubricating oil; m is the mass of the lubricating oil. For component 2 of the thermal system, the lubricating oil tank, the lubricating oil tank exchanges heat with the external environment, the lubricating oil exchanges heat with the tank body through heat conduction, and then the tank body exchanges heat with the external environment through convection. The heat transfer calculation formula for the entire heat exchange process is as follows: In the formula, h1 is the thermal conductivity of air, δ is the thickness of the box wall; t1 is the local atmospheric temperature, which is calculated by interpolation from the table of atmospheric temperature variation with altitude in the literature; t2 is the temperature of the inner wall of the lubricating oil box, A′ is the heat conduction area, which is equal to the surface area of ​​the lubricating oil box in this case, and λ is the thermal conductivity of the box body. For the thermal system components 3, the servo fuel heater and the fuel oil radiator, the lubrication system adopts a shell-and-tube servo fuel heater and a fuel oil radiator. The heat exchange efficiency η is obtained by interpolating the heat exchange characteristic test data of the radiator. The definition of heat transfer efficiency in relevant experiments is shown in the following formula: In the formula, η is the heat transfer efficiency, and T 滑入 T represents the radiator inlet lubricating oil temperature. 燃入 T represents the fuel temperature at the radiator inlet. 滑出 This refers to the lubricating oil temperature at the radiator outlet. For iterative algorithm modeling of thermal systems: a lubricating oil supply temperature T is set. 滑出 Given the engine operating parameters as high-pressure rotor speed N2, the heat generated by the three bearings in the front bearing cavity (H1, H2, H3), the heat generated by the middle bearing cavity (H4), the heat generated by the rear bearing cavity (H5), and the heat generated by the three gearboxes (H6, H7, H8) are calculated using formula (33). The sum of the heat generated by the bearings and gears is the engine heat generated H. The flow rate Q of the front bearing cavity is obtained from the oil return system. 前 Flow rate Q in the bearing cavity 中 Flow rate Q in the rear bearing cavity 后 and gearbox flow rate Q 齿 The temperature rise ΔT of the lubricating oil flowing through the engine is calculated by formula (34), and the return oil temperature T after the lubricating oil flows through the heat-generating components is then calculated by formula (34). 回油 : T 回油 =T 滑出 +ΔT (37) Then, calculate the heat dissipation φ in the lubricating oil tank according to formula (35), and combine it with the fuel flow rate W at the radiator inlet and the lubricating oil temperature T at the radiator outlet. 滑出 The heat dissipation q in the lubricating oil radiator and the servo fuel heater can be calculated. q=WC P (T 滑入 -T 滑出 ) (38) Where W is the fuel flow rate at the radiator inlet, and C P Given the specific heat capacity of the lubricating oil and the radiator inlet fuel temperature T... 滑入 T 滑出 This refers to the lubricating oil temperature at the radiator outlet. The heat transfer efficiency η value is interpolated from the heat transfer characteristic test data of the radiator and substituted into formula (36) to calculate the temperature of the lubricating oil after heat dissipation through the heat dissipation component, and the new lubricating oil supply temperature T is obtained again. 滑出 The oil supply temperature is compared with the previously assumed value. If they are equal, the iteration ends; otherwise, the assumed value is corrected and the iteration starts again. Step 5: Modeling the entire system The entire lubricating oil system is based on the subsystem model established in steps 1, 2, 3, and 4, and coordinates the data interaction between subsystems: the calculation of the oil supply system depends on the front bearing cavity pressure P output by the ventilation system. d1 , middle bearing cavity pressure P d2 Rear bearing cavity pressure P d3 and gearbox pressure P d4 The calculations for the return oil system and the thermal system depend on the calculated outlet pressure P after the oil supply pump in the oil supply system. pump_out Total lubricating oil supply Q d_all Front bearing cavity nozzle flow rate Q d1 Flow rate Q of nozzle in bearing cavity d2 , Rear bearing cavity nozzle flow rate Q d3 and gearbox nozzle flow rate Q d4 The oil supply temperature T calculated by the thermal system 滑出 Oil return temperature T 回油 It also affects the lubricating oil density ρ and lubricating oil kinematic viscosity μ of the oil supply and return, thus forming a complete system model calculation that integrates the oil supply system and the oil return system; The input parameters of the whole system model are mainly related to the engine operating conditions and the pressure before the grating seal at each location. Pressure after the fangs are sealed Temperature before sealing the teeth High-pressure rotor speed N2, low-pressure rotor speed N3, and flight altitude H fly The sealing structure parameters include the number of teeth N, tooth tip thickness t, sealing gap c, flow area A, and pressure before sealing. Pressure after the fangs are sealed Temperature before sealing the teeth The temperature was calculated using a ventilation model to obtain the front bearing cavity pressure P. d1 , middle bearing cavity pressure P d2 Rear bearing cavity pressure P d3 Gearbox pressure P d4 The lubricating oil tank pressure P obtained from the return oil model tank High-pressure rotor speed N2, radiator inlet fuel flow rate W, and radiator inlet fuel temperature T 滑入 The lubricating oil supply temperature T was calculated using a thermodynamic model. 滑出 Oil return temperature T 回油 Then, by substituting these two output parameters into the formulas (3) and (20) of the oil circuit system model, the supply / return oil flow rate, lubricating oil supply pressure, and supply / return oil temperature parameters at each oil circuit of the system are obtained. Step 6: Perform full-system fault simulation for common faults in the lubricating oil system. The fault model considers the entire system model, the mechanism of lubricating oil system failure, and the changes in characteristic parameters of pump, oil filter, and radiator conduit components during failure, as well as the resulting changes in measuring point parameters. This leads to seven types of faults: pump shaft breakage, oil-gas separator damage, fuel supply filter blockage, servo fuel heater fuel leakage, lubricating oil radiator line blockage, fuel radiator fuel leakage, and main return oil filter blockage. The volumetric efficiency η of the fuel supply pump is also selected. v Oil level in the lubricating tank (h), oil filter flow resistance (Δp) b Lubricating oil main flow rate Q all _ 回油 Heat exchange efficiency η, engine heat generation H, lubricating oil circuit flow resistance Δp c2 Oil filter flow resistance Δp f Eight characteristic parameters were adjusted and set, and the parameter values ​​at the measuring points were calculated through simulation. The specific simulation adjustment settings for various faults are shown in Table 1 below: Table 1 Fault Characteristic Parameters and Adjustment Settings Finally, the parameter values ​​calculated through simulation can reproduce the changes in component performance parameters and measurement point signals corresponding to seven types of faults, including pump shaft breakage, damage to the oil-gas separator, blockage of the oil supply filter, blockage of the oil return filter, fuel leakage from the servo fuel heater, fuel leakage from the lubricating oil radiator, and blockage of the lubricating oil radiator. This allows for the establishment of a fault model and the completion of fault simulation for the lubricating oil system.

2. A computer system, characterized in that... include: One or more processors, a computer-readable storage medium for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method of claim 1.

3. A computer-readable storage medium, characterized in that... The device stores computer-executable instructions, which, when executed, are used to implement the method of claim 1.

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