CN112528492A - Fault detection method and device under wing damage condition - Google Patents

Fault detection method and device under wing damage condition Download PDF

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CN112528492A
CN112528492A CN202011429515.5A CN202011429515A CN112528492A CN 112528492 A CN112528492 A CN 112528492A CN 202011429515 A CN202011429515 A CN 202011429515A CN 112528492 A CN112528492 A CN 112528492A
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coefficient
airplane
lift coefficient
fault
identification
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CN112528492B (en
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刘永臻
周大鹏
杨大鹏
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Shenyang Aircraft Design and Research Institute Aviation Industry of China AVIC
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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Abstract

The application provides a fault detection method under the condition of wing damage, which comprises the following steps: according to a kinetic equation of the airplane, an expression of aerodynamic force and aerodynamic moment coefficients of the airplane about measurable state quantity is reversely solved, and a lift coefficient identification model is constructed by combining an aerodynamic moment coefficient model of the airplane; identifying the lift coefficient on line by using a limited memory least square method; and comparing the lift coefficient obtained by identification with wind tunnel test data, judging the fault type position and calculating the fault severity. According to the fault detection method, due to the fact that the online parameter identification fault diagnosis method is adopted, after the fault occurs, the system for detecting the fault can quickly and accurately diagnose the fault, subsequently, the remaining flight capacity can be evaluated based on the diagnosis result, the flight control law can be reconstructed, and the flight safety is improved.

Description

Fault detection method and device under wing damage condition
Technical Field
The application belongs to the technical field of airplane fault detection, and particularly relates to a fault detection method and device under the condition of wing damage.
Background
When an airplane breaks down, emergency treatment work such as pilot warning, auxiliary decision, control reconstruction and the like needs to be carried out, and the development of the work depends on accurate fault diagnosis results.
In the prior art, fault diagnosis is mainly performed on redundancy management of a flight management system, and the flight management system can only know whether a certain sensor or actuator has a fault, but cannot know the severity of the fault, so that when faults such as control surface actuation limitation and airfoil damage occur, the flight management system is difficult to perform fault emergency treatment in a targeted manner.
Disclosure of Invention
The present application is directed to a method and apparatus for fault detection in the event of wing damage, to address or mitigate at least one of the problems in the background art.
In one aspect, the present application provides a fault detection method in the event of a wing damage, the fault detection method comprising:
according to a kinetic equation of the airplane, an expression of aerodynamic force and aerodynamic moment coefficients of the airplane about measurable state quantity is reversely solved, and a lift coefficient identification model is constructed by combining an aerodynamic moment coefficient model of the airplane;
identifying the lift coefficient on line by using a limited memory least square method;
and comparing the lift coefficient obtained by identification with wind tunnel test data, judging the fault type position and calculating the fault severity.
Further, the process of constructing the lift coefficient identification model includes:
calculating a projection component Z of the total external force borne by the airplane on an OZ axis of a coordinate system of the airplane according to an airplane mass center kinetic equation:
Figure BDA0002826109630000021
in the formula, m is the mass of the airplane, and u, v and w are the triaxial velocity components under the shafting of the airplane body;
the resultant external force on the airplane is decomposed into aerodynamic force, engine thrust and gravity, and the aerodynamic force, the engine thrust and the gravity are projected on an OZ axis to obtain
Figure BDA0002826109630000022
In the formula, T is the thrust of the engine,
Figure BDA0002826109630000023
for engine mounting angle, Lba-3Third row of the transformation matrix for the axis of the air flow to the axis of the body, FairThe angle is a pitch angle, and phi is a roll angle;
in the above formula, Lba-3＝[sin α cos β-sin α sin β cos α]
Aerodynamic force FairExpressed as: fair＝0.5ρV2Sref[-CD CC -CL]T
In the formula, CDIs a coefficient of resistance, CCIs the coefficient of lateral force, CLIs the coefficient of lift;
according to the formula:
Figure BDA0002826109630000024
the aerodynamic coefficient equation obtained after finishing is as follows:
CL-cf＝ψL-cfεL-cf+vL-cf
in the formula:
Figure BDA0002826109630000025
ψL-cf＝0.5ρV2Sref[sin α cos β-sin α sin β cos α]，εL-cf＝[-CD,CC,-CL]T，vL-cfto measure noise;
through multiple sampling of flight state parameters, an nth group of aerodynamic coefficient equations are constructed as follows:
Figure BDA0002826109630000026
based on the derivation, the lift coefficient identification model constructed is:
LL-cf＝ΨL-cfεL-cf+VL-cf
wherein L isL-cfIs a vector consisting of the components of the aircraft aerodynamic force on the axis OZ of the body axis:
Figure BDA0002826109630000027
ΨL-cffor the aircraft state quantity information matrix:
Figure BDA0002826109630000031
εL-cfvector formed by aerodynamic coefficients to be identified: epsilonL-cf＝[-CD,CC,-CL]T
Vl-cfFor the vector consisting of measurement noise:
Figure BDA0002826109630000032
further, the process of identifying the lift coefficient on line by using the limited memory least square method comprises the following steps:
constructing an index function according to the principle of least squares:
Figure BDA0002826109630000033
in the formula (I), the compound is shown in the specification,
Figure BDA0002826109630000034
is epsilonl-cfAn estimated value of (d);
to make the index function JL-cfMinimum, estimated value
Figure BDA0002826109630000035
Satisfies the following conditions:
Figure BDA0002826109630000036
in the formula, ΨL-cf +Is ΨL-cfThe generalized inverse of (1).
Further, the process of comparing the lift coefficient obtained by identification with the wind tunnel test data, judging the fault type position and calculating the fault severity degree comprises the following steps:
determining a mathematical model of a lift coefficient obtained by a wind tunnel test:
Figure BDA0002826109630000037
when the airfoil of the airplane has no fault, the lift coefficient obtained by identification is approximately equal to the lift coefficient in the wind tunnel test data;
when the damage fault of the single-side airfoil surface occurs, the lift coefficient C is identifiedL *Will be less than the lift coefficient C obtained by the wind tunnel testLWith increasing airfoil failure rate, CLAnd CL *The numerical difference of (a) is also getting larger and larger;
identification error coefficient delta C between lift coefficient obtained by identification and lift coefficient obtained by wind tunnel testLPositive correlation is formed with the wing surface damage rate, and the error coefficient delta C is identified through calculationLEstablishing an identification error coefficient Δ CLAnd the functional relation with the wing surface damage rate can estimate the damage rate of the airplane wing surface through the lift coefficient identification result after the fault occurs.
In another aspect, the present application provides a fault detection device in the event of a wing damage, the fault detection device comprising:
the model construction module is used for reversely solving the expression of aerodynamic force and aerodynamic moment coefficients of the airplane about the measurable state quantity according to the kinetic equation of the airplane and constructing a lift coefficient identification model by combining an aerodynamic moment coefficient model of the airplane;
the coefficient identification module is used for identifying the lift coefficient on line according to a limited memory least square method;
and the fault judgment module is used for comparing the lift coefficient obtained by identification with the wind tunnel test data, judging the fault type position and calculating the fault severity.
Further, the process of constructing the lift coefficient identification model by the model construction module comprises:
calculating a projection component Z of the total external force borne by the airplane on an OZ axis of a coordinate system of the airplane according to an airplane mass center kinetic equation:
Figure BDA0002826109630000041
in the formula, m is the mass of the airplane, and u, v and w are the triaxial velocity components under the shafting of the airplane body;
the resultant external force on the airplane is decomposed into aerodynamic force, engine thrust and gravity, and the aerodynamic force, the engine thrust and the gravity are projected on an OZ axis to obtain
Figure BDA0002826109630000042
In the formula, T is the thrust of the engine,
Figure BDA0002826109630000043
for engine mounting angle, Lba-3Third row of the transformation matrix for the axis of the air flow to the axis of the body, FairThe angle is a pitch angle, and phi is a roll angle;
in the above formula, Lba-3＝[sin α cos β-sin α sin β cos α]
Aerodynamic force FairExpressed as: fair＝0.5ρV2Sref[-CD CC -CL]T
In the formula, CDIs a coefficient of resistance, CCIs the coefficient of lateral force, CLIs the coefficient of lift;
according to the formula:
Figure BDA0002826109630000044
the aerodynamic coefficient equation obtained after finishing is as follows:
CL-cf＝ψL-cfεL-cf+vL-cf
in the formula:
Figure BDA0002826109630000045
ψL-cf＝0.5ρV2Sref[sin α cos β-sin α sin β cos α]，εL-cf＝[-CD,CC,-CL]T，vL-cfto measure noise;
through multiple sampling of flight state parameters, an nth group of aerodynamic coefficient equations are constructed as follows:
Figure BDA0002826109630000051
based on the derivation, the lift coefficient identification model constructed is:
LL-cf＝ΨL-cfεL-cf+VL-cf
wherein L isL-cfIs a vector consisting of the components of the aircraft aerodynamic force on the axis OZ of the body axis:
Figure BDA0002826109630000052
ΨL-cffor the aircraft state quantity information matrix:
Figure BDA0002826109630000053
εL-cfvector formed by aerodynamic coefficients to be identified: epsilonL-cf＝[-CD,CC,-CL]T
Vl-cfFor the vector consisting of measurement noise:
Figure BDA0002826109630000054
further, the process of identifying the lift coefficient on line by the coefficient identification module by limiting a memory least square method comprises the following steps:
constructing an index function according to the principle of least squares:
Figure BDA0002826109630000055
in the formula (I), the compound is shown in the specification,
Figure BDA0002826109630000056
is epsilonl-cfAn estimated value of (d);
to make the index function JL-cfMinimum, estimated value
Figure BDA0002826109630000057
Satisfies the following conditions:
Figure BDA0002826109630000058
in the formula, ΨL-cf +Is ΨL-cfThe generalized inverse of (1).
Furthermore, the process of comparing the lift coefficient obtained by the fault judgment module through identification with the wind tunnel test data, judging the fault type position and calculating the fault severity degree comprises the following steps:
determining a mathematical model of a lift coefficient obtained by a wind tunnel test:
Figure BDA0002826109630000059
when the airfoil of the airplane has no fault, the lift coefficient obtained by identification is approximately equal to the lift coefficient in the wind tunnel test data;
when the damage fault of the single-side airfoil surface occurs, the lift coefficient C is identifiedL *Will be less than the lift coefficient C obtained by the wind tunnel testLWith increasing airfoil failure rate, CLAnd CL *The numerical difference of (a) is also getting larger and larger;
identification error coefficient delta C between lift coefficient obtained by identification and lift coefficient obtained by wind tunnel testLPositive correlation is formed with the wing surface damage rate, and the error coefficient delta C is identified through calculationLEstablishing an identification error coefficient Δ CLFunctional relation with airfoil breakage rate, namely identifying result through lift coefficient after fault occursAnd estimating the damage rate of the airplane airfoil.
According to the fault detection method, due to the fact that the online parameter identification fault diagnosis method is adopted, after the fault occurs, the system for detecting the fault can quickly and accurately diagnose the fault, subsequently, the remaining flight capacity can be evaluated based on the diagnosis result, the flight control law can be reconstructed, and the flight safety is improved.
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In order to more clearly illustrate the technical solutions provided by the present application, the following briefly introduces the accompanying drawings. It is to be expressly understood that the drawings described below are only illustrative of some embodiments of the invention.
Fig. 1 is a schematic flow chart of a fault detection method according to the present application.
Fig. 2 is a schematic diagram of the fault detection apparatus according to the present application.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application.
The method for detecting the faults under the condition of wing damage provided by the application adopts a parameter identification method, key parameters such as the control derivative of a control surface, the lift coefficient of an airplane and the like which can reflect the health condition of the airplane are respectively identified in real time, and the diagnosis of the faults is completed by comparing with airborne wind tunnel test data, namely the type, the position and the degree of the faults are confirmed.
As shown in fig. 1, the method for detecting a fault in the case of a wing damage according to the present application mainly includes three steps:
s1, constructing an identification model of the lift coefficient
Firstly, according to a kinetic equation of the airplane, an expression of aerodynamic force and aerodynamic moment coefficients of the airplane about measurable state quantity is reversely solved, and an identification model of a lift coefficient is obtained by combining an aerodynamic moment coefficient model of the airplane.
Specifically, calculating the OZ axis projection component Z of the total external force borne by the airplane in an airplane coordinate system according to an airplane mass center kinetic equation:
Figure BDA0002826109630000071
in the formula, m is the mass of the airplane, and u, v and w are the three-axis velocity components of the shafting of the airplane body.
The external force borne by the airplane can be decomposed into aerodynamic force, engine thrust and gravity, and the aerodynamic force, the engine thrust and the gravity are projected on an OZ axis:
Figure BDA0002826109630000072
in the formula, T is the thrust of the engine,
Figure BDA0002826109630000073
for engine mounting angle, Lba-3And the third row of the conversion matrix from the airflow shafting to the body shafting is shown as the formula (3), Fair is aerodynamic force, and theta and phi are a pitch angle and a roll angle.
Lba-3＝[sin α cos β-sin α sin β cos α] (3)
Aerodynamic force Fair can be expressed as: fair＝0.5ρV2Sref[-CD CC -CL]T (4)
In the formula, CDIs a coefficient of resistance, CCIs the coefficient of lateral force, CLIs the lift coefficient.
The substitution of formulae (1), (3) and (4) for formula (2) can be obtained:
Figure BDA0002826109630000074
the aerodynamic coefficient equation obtained by sorting the above formula is as follows:
CL-cf＝ψL-cfεL-cf+vL-cf (5)
wherein:
Figure BDA0002826109630000075
ψL-cf＝0.5ρV2Sref[sin α cos β-sin α sin β cos α]
εL-cf＝[-CD,CC,-CL]T
vL-cfto measure noise.
Through multiple sampling of flight state parameters, an nth group of aerodynamic coefficient equations are constructed as follows:
Figure BDA0002826109630000081
based on the above derivation, an identification model of the lift coefficient can be constructed as follows:
LL-cf＝ΨL-cfεL-cf+VL-cf (7)
wherein L isL-cfIs a vector consisting of the components of the aircraft aerodynamic force on the axis OZ of the body axis:
Figure BDA0002826109630000082
ΨL-cffor the aircraft state quantity information matrix:
Figure BDA0002826109630000083
εL-cfvector formed by aerodynamic coefficients to be identified: epsilonL-cf＝[-CD,CC,-CL]T
Vl-cfFor the vector consisting of measurement noise:
Figure BDA0002826109630000084
s2, identifying lift coefficient on line
And then, identifying key parameters on line by using a limited memory least square method.
The specific process comprises the following steps:
when each flight state parameter sensor of the airplane has no fault, the measurement can be consideredVolume noise VL-cfIs a high frequency signal that follows a normal distribution. In this case, the least square method identifies the derived roll steering derivative vector
Figure BDA0002826109630000085
Is to the actual lift coefficient epsilon of the aircraftL-cfAn unbiased estimation of (1).
The term "limited memory" refers to the state quantity information matrix ΨL-cfAnd lift coefficient information matrix LL-cfThe maximum number of sets of stored data is Nlim. When the number of groups of the data stored in the information matrix reaches NlimEvery time a new set of data is stored, the oldest set of data is deleted. In this way, the number of data sets in the information matrix involved in the recognition calculation will remain unchanged and be the most up-to-date data. This aspect can utilize historical data to suppress measurement noise; on the other hand, the effect of historical data before the fault is eliminated quickly, and therefore a new lift coefficient is identified quickly and accurately.
According to the principle of the least square method, the following index functions are constructed:
Figure BDA0002826109630000091
in the formula (I), the compound is shown in the specification,
Figure BDA0002826109630000092
is epsilonl-cfAn estimate of (d).
To make JL-cfAt minimum, then from knowledge of matrix theory, it can be known that:
Figure BDA0002826109630000093
in the above formula, ΨL-cf +Is ΨL-cfThe generalized inverse of (1).
And S3, judging the damage degree of the wing.
And finally, comparing the identified key parameters with wind tunnel test data, judging the fault type position and calculating the fault severity.
The mathematical model of the lift coefficient obtained from the wind tunnel test is:
Figure BDA0002826109630000094
when the airfoil of the airplane has no fault, the lift coefficient obtained by identification is approximately equal to the lift coefficient in the wind tunnel test data.
When the damage fault of the single-side wing surface occurs, parameters such as wing area, mass, aerodynamic coefficient and the like of the airplane can be changed, wherein the maximum influence on the lift force is the reduction of the wing area, and because the wing area in the identification model is taken as the wing reference area of the example airplane and is a constant, the wing reference area cannot be changed in the identification process, the lift force coefficient C obtained by identification is not changed, so that the lift force coefficient C is obtained by identificationL *Will be less than the lift coefficient C obtained by the wind tunnel testLAlong with the increase of the damage rate of the airfoil, the lift coefficient C obtained by the wind tunnel testLAnd the lift coefficient C obtained by identificationL *The numerical difference of (a) is also getting larger and larger. Lift coefficient C obtained by wind tunnel testLAnd the lift coefficient C obtained by identificationL *Is identified by the error coefficient Delta CLPositive correlation is formed with the wing surface damage rate, and the error coefficient delta C is identified through calculationLEstablishing Δ CLAnd the functional relation with the wing surface damage rate can estimate the damage rate of the airplane wing surface through the lift coefficient identification result after the fault occurs.
According to the fault detection method under the condition of wing damage, due to the design of online parameter identification fault diagnosis, after a fault occurs, the system of the flying pipe can quickly and accurately diagnose the fault, and then the remaining flying capacity can be evaluated and the flying control law can be reconstructed based on the diagnosis result, so that the flying safety is improved.
In addition, the present application also provides a fault detection device in the case of damage to a wing, as shown in fig. 2, the fault detection device 10 includes:
the model construction module 11 is used for reversely solving an expression of aerodynamic force and aerodynamic moment coefficients of the airplane about the measurable state quantity according to a kinetic equation of the airplane, and constructing a lift coefficient identification model by combining an aerodynamic moment coefficient model of the airplane;
the coefficient identification module 12 is used for identifying the lift coefficient on line according to a limited memory least square method;
and the fault judgment module 13 is used for comparing the lift coefficient obtained by identification with wind tunnel test data, judging the fault type position and calculating the fault severity.
Finally, there is also provided in the present application a computer device comprising: one or more processors; storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the fault detection method as in any one of the above.
An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the fault detection method according to any one of the above.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps, methods, apparatuses or modules may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (10)

1. A method of fault detection in the event of damage to an airfoil, the method comprising:
according to a kinetic equation of the airplane, an expression of aerodynamic force and aerodynamic moment coefficients of the airplane about measurable state quantity is reversely solved, and a lift coefficient identification model is constructed by combining an aerodynamic moment coefficient model of the airplane;
identifying the lift coefficient on line by using a limited memory least square method;
and comparing the lift coefficient obtained by identification with wind tunnel test data, judging the fault type position and calculating the fault severity.
2. The method of claim 1, wherein constructing the lift coefficient identification model comprises:
calculating a projection component Z of the total external force borne by the airplane on an OZ axis of a coordinate system of the airplane according to an airplane mass center kinetic equation:
Figure FDA0002826109620000011
in the formula, m is the mass of the airplane, and u, v and w are the triaxial velocity components under the shafting of the airplane body;
the resultant external force on the airplane is decomposed into aerodynamic force, engine thrust and gravity, and the aerodynamic force, the engine thrust and the gravity are projected on an OZ axis to obtain
Figure FDA0002826109620000012
In the formula, T is the thrust of the engine,
Figure FDA0002826109620000013
for engine mounting angle, Lba-3Third row of the transformation matrix for the axis of the air flow to the axis of the body, FairThe angle is a pitch angle, and phi is a roll angle;
in the above formula, Lba-3＝[sinαcosβ -sinαsinβ cosα]
Aerodynamic force FairExpressed as: fair＝0.5ρV2Sref[-CD CC -CL]T
In the formula, CDIs a coefficient of resistance, CCIs the coefficient of lateral force, CLIs the coefficient of lift;
according to the formula:
Figure FDA0002826109620000014
the aerodynamic coefficient equation obtained after finishing is as follows:
CL-cf＝ψL-cfεL-cf+vL-cf
in the formula:
Figure FDA0002826109620000021
ψL-cf＝0.5ρV2Sref[sinαcosβ -sinαsinβ cosα]，εL-cf＝[-CD,CC,-CL]T，vL-cfto measure noise;
through multiple sampling of flight state parameters, an nth group of aerodynamic coefficient equations are constructed as follows:
Figure FDA0002826109620000022
based on the derivation, the lift coefficient identification model constructed is:
LL-cf＝ΨL-cfεL-cf+VL-cf
wherein L isL-cfIs a vector consisting of the components of the aircraft aerodynamic force on the axis OZ of the body axis:
Figure FDA0002826109620000023
ΨL-cffor the aircraft state quantity information matrix:
Figure FDA0002826109620000024
εL-cfvector formed by aerodynamic coefficients to be identified: epsilonL-cf＝[-CD,CC,-CL]T
Vl-cfFor the vector consisting of measurement noise:
Figure FDA0002826109620000025
3. the method of claim 2, wherein the process of identifying the lift coefficient on-line using a constrained memory least squares method comprises:
constructing an index function according to the principle of least squares:
Figure FDA0002826109620000026
in the formula (I), the compound is shown in the specification,
Figure FDA0002826109620000027
is epsilonl-cfAn estimated value of (d);
to make the index function JL-cfMinimum, estimated value
Figure FDA0002826109620000028
Satisfies the following conditions:
Figure FDA0002826109620000029
in the formula, ΨL-cf +Is ΨL-cfThe generalized inverse of (1).
4. The method of claim 3, wherein the step of comparing the identified lift coefficient with the wind tunnel test data, determining the fault type and the fault severity, comprises:
determining a mathematical model of a lift coefficient obtained by a wind tunnel test:
Figure FDA0002826109620000031
when the airfoil of the airplane has no fault, the lift coefficient obtained by identification is approximately equal to the lift coefficient in the wind tunnel test data;
when the damage fault of the single-side airfoil surface occurs, the lift coefficient C is identifiedL *Will be less than the lift coefficient C obtained by the wind tunnel testLWith increasing airfoil failure rate, CLAnd CL *The numerical difference of (a) is also getting larger and larger;
identification error coefficient delta C between lift coefficient obtained by identification and lift coefficient obtained by wind tunnel testLPositive correlation is formed with the wing surface damage rate, and the error coefficient delta C is identified through calculationLEstablishing an identification error coefficient Δ CLAnd the functional relation with the wing surface damage rate can estimate the damage rate of the airplane wing surface through the lift coefficient identification result after the fault occurs.
5. A fault detection device in the event of a wing damage, the fault detection method comprising:
the model construction module is used for reversely solving the expression of aerodynamic force and aerodynamic moment coefficients of the airplane about the measurable state quantity according to the kinetic equation of the airplane and constructing a lift coefficient identification model by combining an aerodynamic moment coefficient model of the airplane;
the coefficient identification module is used for identifying the lift coefficient on line according to a limited memory least square method;
and the fault judgment module is used for comparing the lift coefficient obtained by identification with the wind tunnel test data, judging the fault type position and calculating the fault severity.
6. The apparatus for fault detection in the event of an airfoil damage of claim 5, wherein the process of constructing the lift coefficient identification model by the model construction module comprises:
calculating a projection component Z of the total external force borne by the airplane on an OZ axis of a coordinate system of the airplane according to an airplane mass center kinetic equation:
Figure FDA0002826109620000041
in the formula, m is the mass of the airplane, and u, v and w are the triaxial velocity components under the shafting of the airplane body;
the resultant external force on the airplane is decomposed into aerodynamic force, engine thrust and gravity, and the aerodynamic force, the engine thrust and the gravity are projected on an OZ axis to obtain
Figure FDA0002826109620000042
In the formula, T is the thrust of the engine,
Figure FDA0002826109620000043
for engine mounting angle, Lba-3Third row of the transformation matrix for the axis of the air flow to the axis of the body, FairThe angle is a pitch angle, and phi is a roll angle;
in the above formula, Lba-3＝[sinαcosβ -sinαsinβ cosα]
Aerodynamic force FairExpressed as: fair＝0.5ρV2Sref[-CD CC -CL]T
In the formula, CDIs a coefficient of resistance, CCIs the coefficient of lateral force, CLIs the coefficient of lift;
according to the formula:
Figure FDA0002826109620000044
the aerodynamic coefficient equation obtained after finishing is as follows:
CL-cf＝ψL-cfεL-cf+vL-cf
in the formula:
Figure FDA0002826109620000045
ψL-cf＝0.5ρV2Sref[sinαcosβ -sinαsinβ cosα]，εL-cf＝[-CD,CC,-CL]T，vL-cfto measure noise;
through multiple sampling of flight state parameters, an nth group of aerodynamic coefficient equations are constructed as follows:
Figure FDA0002826109620000046
based on the derivation, the lift coefficient identification model constructed is:
LL-cf＝ΨL-cfεL-cf+VL-cf
wherein L isL-cfIs a vector consisting of the components of the aircraft aerodynamic force on the axis OZ of the body axis:
Figure FDA0002826109620000047
ΨL-cffor the aircraft state quantity information matrix:
Figure FDA0002826109620000048
εL-cfvector formed by aerodynamic coefficients to be identified: epsilonL-cf＝[-CD,CC,-CL]T
Vl-cfFor the vector consisting of measurement noise:
Figure FDA0002826109620000051
7. the apparatus for fault detection in the event of an airfoil damage of claim 1, wherein the coefficient identification module defines a process for online identification of the lift coefficient using a memory least squares method comprising:
constructing an index function according to the principle of least squares:
Figure FDA0002826109620000052
in the formula (I), the compound is shown in the specification,
Figure FDA0002826109620000053
is epsilonl-cfAn estimated value of (d);
to make the index function JL-cfMinimum, estimated value
Figure FDA0002826109620000054
Satisfies the following conditions:
Figure FDA0002826109620000055
in the formula, ΨL-cf +Is ΨL-cfThe generalized inverse of (1).
8. The device for detecting the failure under the condition of wing damage according to claim 1, wherein the process of comparing the lift coefficient obtained by the failure judgment module by identification with the wind tunnel test data, judging the failure type position and calculating the failure severity degree comprises the following steps:
determining a mathematical model of a lift coefficient obtained by a wind tunnel test:
Figure FDA0002826109620000056
when the airfoil of the airplane has no fault, the lift coefficient obtained by identification is approximately equal to the lift coefficient in the wind tunnel test data;
when the damage fault of the single-side airfoil surface occurs, the lift coefficient C is identifiedL *Will be less than the lift coefficient C obtained by the wind tunnel testLWith increasing airfoil failure rate, CLAnd CL *The numerical difference of (a) is also getting larger and larger;
identification error coefficient delta C between lift coefficient obtained by identification and lift coefficient obtained by wind tunnel testLPositive correlation is formed with the wing surface damage rate, and the error coefficient delta C is identified through calculationLEstablishing an identification error coefficient Δ CLAnd the functional relation with the wing surface damage rate can estimate the damage rate of the airplane wing surface through the lift coefficient identification result after the fault occurs.
9. A computer device, comprising:
one or more processors;
storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-4.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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