CN117539227A - Fault diagnosis method for actuator of attitude control system of aircraft - Google Patents
Fault diagnosis method for actuator of attitude control system of aircraft Download PDFInfo
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Abstract
The invention discloses a fault diagnosis method for an actuator of an aircraft attitude control system, and belongs to the technical field of fault diagnosis of actuators of aircraft attitude control systems. The method comprises the steps of establishing an aircraft attitude dynamics model; designing a multi-model volume Kalman filter bank according to an aircraft attitude dynamics model; judging whether an abnormal condition exists in the innovation sequence based on a multi-sample Kalman detection method according to the innovation sequence generated by the multi-model volume Kalman filter bank; if the innovation sequence is judged to be in an abnormal condition based on the multi-sample chi-square test method, judging that the actuator of the attitude system of the aircraft has a fault, and carrying out fault isolation on the fault; and according to the fault isolation and the aircraft attitude dynamics model, designing a consistent convergence fault observer to reconstruct moment level faults and finishing fault reconstruction of an actuator level. The invention can realize accurate fault diagnosis in a short time and provides a basis for realizing the fault recovery of the actuator of the attitude control system of the aircraft.
Description
Technical Field
The invention belongs to the technical field of fault diagnosis of an actuator of an attitude control system of an aircraft, and relates to a fault diagnosis method for the actuator of the attitude control system of the aircraft.
Background
Attitude control systems are one of the most important subsystems of an aircraft, the normality or absence of which will directly affect the ability of the aircraft to perform a given flight mission. However, the aircraft may be in an extreme flight condition, and the severe flight environment may cause the aircraft to be susceptible to wind interference, airflow disturbance, and other factors, so that the attitude control system of the aircraft may be likely to malfunction. The prior research data show that the fault of the actuating mechanism is one of the fault modes with the highest occurrence probability and the most serious consequences in a plurality of fault modes of the aircraft. Therefore, once the attitude control system actuator of the aircraft fails and cannot be processed quickly and accurately, the attitude control system actuator of the aircraft can pose a great threat to the safety of the aircraft. This places high demands on the fault diagnosis method of the aircraft attitude control system actuator.
At present, most researches on fault diagnosis of an actuator of an attitude control system of an aircraft only stay at a moment level, and fault information specific to the actuator level cannot be diagnosed, which is unfavorable for a subsequent recovery technology aiming at faults. Some researches can diagnose the fault information of the actuator level, but many of the researches do not consider the coupling relation of the actuators, and the distribution matrix of the actuators is linearized, so that the fault diagnosis problem of the actuators of the attitude control system of the aircraft is greatly simplified, and the faults of the actuators cannot be accurately detected and isolated in a short time.
Disclosure of Invention
Aiming at the situation that the coupling relation of the actuator is not considered in the prior art, the fault diagnosis problem of the actuator of the attitude control system of the aircraft is greatly simplified, so that the actuator fault can not be accurately detected and isolated in a short time. The invention provides a fault diagnosis method for an actuator of an aircraft attitude control system, which can realize accurate fault detection and fault isolation in a short time and provides a basis for realizing the fault recovery of the actuator of the aircraft attitude control system.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method of fault diagnosis for an aircraft attitude control system actuator, comprising:
establishing an aircraft attitude dynamics model;
designing a multi-model volume Kalman filter bank according to an aircraft attitude dynamics model;
judging whether an abnormal condition exists in the innovation sequence based on a multi-sample Kalman detection method according to the innovation sequence generated by the multi-model volume Kalman filter bank;
if the innovation sequence is judged to be in an abnormal condition based on the multi-sample chi-square test method, judging that the actuator of the attitude system of the aircraft has a fault, and carrying out fault isolation on the fault;
and designing a consistent convergence fault observer reconstruction moment level fault D according to the fault isolation and aircraft attitude dynamics model, and completing the fault reconstruction of the actuator level.
As a further explanation of the present invention, the building of the aircraft attitude dynamics model is specifically performed as follows:
wherein ω represents the attitude angular velocity of the aircraft, J is the aircraft inertia matrix, u d Triaxial moment accepted by the aircraft, D represents comprehensive faults accepted by the aircraft;
comprehensive fault d=j to which the aircraft is subjected -1 d+u f ；
Wherein u is f The moment level fault is suffered by the aircraft, and d is the external interference suffered by the aircraft.
As a further explanation of the invention, the system establishes a fault-free state space equation according to the aircraft attitude dynamics model, and discretizes the fault-free state space equation to obtain a discrete total state space equation;
the output quantity of the actuator is amplified to a discrete total state space equation to obtain an amplified state space equation;
a multi-model volume Kalman filter bank is designed based on the discrete total state space equation and the augmented state space equation.
As a further explanation of the present invention, the innovation sequences generated according to the multi-model volume kalman filter set are m+1 sets, where m is the number of actuators, and the innovation sequences specifically represent the following:
wherein,new information representing the total filter at time k, < ->Represents the measurement vector estimate at the kth moment of the total filter, for>Innovation indicating sub-filter i at time k, < ->Representing the measurement vector estimate at the kth time of the sub-filter i.
As a further explanation of the invention, the method for judging whether the new information sequence has abnormal conditions based on the multi-sample chi-square test method is to construct new informationBased on the new information->Constructing the statistics obtained->Judging whether the new information sequence has abnormal conditions or not;
if statistics areIf the value is smaller than the set threshold value, no abnormal condition exists in the innovation sequence;
if statistics areIf the value is larger than the set threshold value, the information sequence has abnormal conditions.
As a further explanation of the invention, the new information:
wherein,representing the j new innovation, N representing the length of a multi-sample inspection window;
the new information is based onConstructing the obtained statistics:
wherein,representing new innovation->Covariance matrix of>Representing new information->The covariance matrix is calculated in the filtering process.
As a further explanation of the present invention, if the multi-sample chi-square test method determines that the innovation sequence is abnormal, it is determined that the actuator of the attitude system of the aircraft has a fault, and then:
judging the new information in the new information sequenceWhether or not there is an abnormality;
if new is aboutAnd if no abnormality exists, judging that the ith actuator fails, and completing fault isolation.
As a further explanation of the invention, according to the fault isolation and the aircraft attitude dynamics model, a consistent convergence fault observer is designed to reconstruct a moment level fault D, an objective function is designed, and the objective function is optimized, so that the fault reconstruction of an actuator level is completed.
As a further explanation of the present invention, the specific expression of the objective function is as follows:
wherein, lambda n (r) represents the matrix I m×m The n-th diagonal term of (a) is replaced by r to obtain a matrix, n represents the n-th actuator fault, Q 1 ∈R 3×3 Representing a matrix of weight coefficients.
As a further explanation of the invention, the multi-sample chi-square test method is used for judging whether the innovation sequence has abnormal conditions, and if the multi-sample chi-square test method is used for judging that the innovation sequence has no abnormal conditions, all the executors are judged to be normal, fault isolation and fault reconstruction are not needed, and fault diagnosis is directly finished.
Compared with the prior art, the invention has the following beneficial effects.
The invention discloses a fault diagnosis method for an aircraft attitude control system actuator, which is characterized in that an aircraft attitude dynamics model is established, a multi-model volume Kalman filter bank is designed, multi-sample chi-square inspection is performed based on a innovation sequence generated by the filter bank, and fault detection and fault isolation of the aircraft attitude system actuator are realized according to inspection results. The volume Kalman filter can process a system with strong nonlinearity like a complex aircraft, and the jacobian matrix is not calculated like an extended Kalman filter, so that the operation is simple. Therefore, the invention can accurately detect and isolate the fault of the actuator in a short time, avoid aviation accidents, provide a basis for the subsequent realization of fault recovery of the actuator of the attitude control system of the aircraft, improve the safety and reliability of the aircraft and reduce the adverse consequences caused by the fault of the aircraft. According to fault isolation information and a designed consistent convergence fault observer, reconstructing moment level faults, designing an objective function, reconstructing actuator level faults through optimizing the function, enabling a fixed-time high-order sliding mode fault observer to achieve fixed-time convergence, and rapidly and accurately reconstructing system faults without considering an initial value range.
Drawings
FIG. 1 is a flow chart of a method of fault diagnosis for an aircraft attitude control system actuator according to the present invention;
FIG. 2 is a flow chart of an actuator fault diagnosis for an aircraft attitude control system embodying the present invention;
FIG. 3 is a graph of the overall filter failure detection results of the present invention;
FIG. 4 is a graph of the sub-filter bank fault isolation results of the present invention;
FIG. 5 is a torque level fault reconstruction graph of the present invention;
FIG. 6 is a graph of torque level fault reconstruction error for the present invention;
FIG. 7 is a graph of an actuator level fault reconstruction of the present invention.
Detailed Description
The invention will be described in detail below with reference to the drawings in connection with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
The following detailed description is exemplary and is intended to provide further details of the invention. Unless defined otherwise, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the invention.
Aiming at the problem that the coupling relation of the actuator is not considered in the prior art, the fault diagnosis problem of the actuator of the attitude control system of the aircraft is greatly simplified, so that the fault of the actuator cannot be accurately detected and isolated in a short time. The invention provides a fault diagnosis method for an actuator of an attitude control system of an aircraft, as shown in fig. 1, which comprises the following steps:
establishing an aircraft attitude dynamics model;
designing a multi-model volume Kalman filter bank according to an aircraft attitude dynamics model;
judging whether an abnormal condition exists in the innovation sequence based on a multi-sample Kalman detection method according to the innovation sequence generated by the multi-model volume Kalman filter bank;
if the innovation sequence is judged to be in an abnormal condition based on the multi-sample chi-square test method, judging that the actuator of the attitude system of the aircraft has a fault, and carrying out fault isolation on the fault;
and according to the fault isolation and the aircraft attitude dynamics model, designing a consistent convergence fault observer to reconstruct moment level faults and finishing fault reconstruction of an actuator level.
The invention is described in detail below with reference to the attached drawings:
as shown in fig. 2, the invention provides a fault diagnosis method for an actuator of an attitude control system of an aircraft, which comprises the following steps:
s1, building an aircraft attitude dynamics model containing actuator faults and interferences, wherein the aircraft attitude dynamics model comprises the following steps:
wherein ω εR 3×1 Representing the attitude angular velocity of an aircraft, J is an aircraft inertia matrix, u d Triaxial moment, d=j, for aircraft theory -1 d+u f Indicating the general failure to which the aircraft is subjected, u f The moment level fault is suffered by the aircraft, and d is the external interference suffered by the aircraft. The triaxial moment to which the aircraft is subjected and its failure are expressed as:
u d ＝f(δ)
u f ＝f(Λδ)-f(δ)
where f () is a function representing the actuator distribution, δ= [ δ ] 1 ,...,δ m ] T Represents the theoretical value of the actuator output vector, m is the number of actuators, Λ=diag { λ } 1 ,...,λ m }∈R m×m To represent the failure degree coefficient matrix of the failure fault of the actuator part, 0 is less than or equal to lambda i ≤1。
S2, according to the aircraft attitude dynamics model established in the S1, establishing a fault-free state space equation as follows:
z＝Hx+v
wherein, A= -J -1 ω×J，g(u)＝J -1 f (u), x=ω represents a system state vector, u=δ represents a system input vector, w represents a system noise vector, z represents a system measurement vector, h=i 3×3 Representing a matrix of measurement coefficients, v representing a measurement noise vector. The discretized state space equation is:
x k ＝x k-1 +Ax k-1 T s +g(u k-1 )T s +w k-1
z k ＝Hx k +v k
wherein x is k 、x k-1 Representing the system state vectors at the k-th and k-1 times respectively,representing the system input vector at time k-1, T s For sampling step length, w k-1 Representing the system noise vector, z at time k-1 k Representing the system measurement vector at the kth time, v k Representing the measurement noise vector at the kth time.
S3, according to the total state space equation established in the S2, the output quantity of the actuator is amplified to the state space equation to obtain m amplified state space equations, wherein the i (i=1, the m) th equation is:
wherein,for augmentation of state vector +.>To amplify system noise, the actuator output is considered herein to be a random walk, ζ k-1 H is the noise output by the actuator i ＝[I 3×3 0 3×1 ]Function ofThe method comprises the following steps:
wherein,use->(4) Replace u k-1 Is->Obtain->
S4, designing a multi-model volume Kalman filter group which comprises m+1 volume Kalman filters in total according to the state space equations established in the S2 and the S3, wherein the filters are different in the specific state space equations, and the corresponding relation is specifically as follows:
total filter-discrete total state space equation
sub-Filter 1-1 st augmented state space equation
……
Sub-filter m-mth augmented state space equation
The innovation sequences generated by the designed volume Kalman filter group are m+1 groups in total, and specifically are:
wherein,new information representing the total filter at time k, < ->Represents the measurement vector estimate at the kth moment of the total filter, for>Represents the kth timeInnovation of the notch filter i +.>Representing the measurement vector estimate at the kth time of the sub-filter i.
S5, judging the abnormal condition of the innovation sequence based on a multi-sample chi-square test method according to the multi-model volume Kalman filter set designed in the S4, and constructing new innovation firstly, wherein the method specifically comprises the following steps:
wherein,representing the j-th innovation, N represents the multi-sample test window length, and the statistics are further constructed:
wherein,representing new innovation->Covariance matrix of V k j Representing new information->The covariance matrix is calculated in the filtering process.
Statistics based on constructionJudging abnormal conditions of the innovation sequence, specifically:
threshold of reasonable designIf->Then represent the current innovation->No abnormality; on the contrary, if->Then represent the current innovation->There is an abnormality.
S6, according to the method for judging the abnormal condition of the innovation sequence based on the multi-sample chi-square test method in S5, fault detection and fault isolation are realized by judging the abnormal condition of the innovation sequence, and the method comprises the following steps:
first, judge the innovationWhether or not there is an abnormality. If new is->If the fault exists, judging that the fault condition of the actuator exists, and completing fault detection, wherein fault isolation is required to be carried out through a second step; and otherwise, judging that all the actuators are normal, finishing fault detection and finishing fault diagnosis.
Second, judge the innovationWhether or not there is an abnormality. If only new information->And if no abnormality exists, judging that the ith actuator fails, and completing fault isolation.
S7, according to the aircraft attitude dynamics model designed in the S1, a consistent convergence fault observer reconstruction moment level fault D is designed, and specifically:
wherein, kappa i And k i (i=1, …, 4) are all parameters to be designed, and the Hurwitz condition, parameter alpha, needs to be met i ＝ia-(i-1)，a∈(1-ε 1 1), parameter beta i ＝ib-(i-1)，b∈(1,1+ε 2 )，ε 1 And epsilon 2 Are all extremely small, function sig r (x)＝|x| r ·sgn(x)，z i Representing the amount of process in the observer, z 2 Will converge to the integrated fault quantity D in a fixed time.
S8, designing an objective function according to the fault isolation information obtained in the S6 and the moment level fault reconstructed in the S7, wherein the objective function specifically comprises the following steps:
wherein, lambda n (r) represents the matrix I m×m The n-th diagonal term of (a) is replaced by r to obtain a matrix, n represents the n-th actuator fault, Q 1 ∈R 3×3 Representing a matrix of weight coefficients. Further, the optimization problem can be described as:
wherein r.epsilon.0, 1 represents the actuator failure coefficient. By solving this optimization problem, a fault reconstruction of the actuator hierarchy can be achieved.
The following describes a specific calculation process of the fault diagnosis method for the aircraft attitude control system actuator through Matlab simulation.
The simulation parameters were set as follows:
the aircraft specific parameters are: inertia matrixReference area S ref ＝149.39m 2 Span b=11.16m, wing chord length c=19.26m, number of actuators is 8, each actuator actuation range delta min ＝[-30,-30,-30,-30,-15,-15,-60,-30]，δ max ＝[30,30,30,30,26,26,30,60]The relationship between each actuator output and the triaxial moment coefficient is shown in tables 1 to 3.
TABLE 1 output and roll moment coefficient relationship for actuators
Table 2 actuator output and pitch moment coefficient relationship
TABLE 3 actuator output versus yaw moment coefficient
The relevant parameters of flight simulation are as follows: the flight time is 15s, the simulation step length is 0.01s, the interference moment is Gaussian white noise with zero mean value, the standard deviation is 100N, the measurement noise is Gaussian white noise with zero mean value, and the standard deviation is 1 multiplied by 10 -6 (rad/s)。
The fault-related parameters are: the occurrence time of the fault is 10s, the occurrence position of the fault is the actuator 1 or the actuator 2, the failure degree of the actuator is 0.5, and the fault detection threshold T is D ＝0.1。
The volume kalman filter set parameters are: total filter system noise covariance matrix Q 0 ＝diag{1×10 -8 ,1×10 -8 ,1×10 -8 Noise covariance matrix Q of sub-filter system i ＝diahg{1×10 -7 ,1×10 -7 ,1×10 -7 ,1×10 -2 Measure noise covariance matrix r=diag {1×10 } -8 ,1×10 -8 ,1×10 -8 }。
The consistent convergence observer parameters were: a=0.8, b=1.2, κ 1 ＝k 1 ＝3，κ 2 ＝k 2 ＝4.16，κ 3 ＝k 3 ＝3.06，κ 4 ＝k 4 ＝1.1。
The optimization objective function parameters are as follows: q (Q) 1 ＝I 3 。
As can be seen from the correspondence between the actuator outputs and the moment coefficients in tables 1 to 3, the correspondence between the actuator 1 and the actuator 2 is identical, which means that the fault expression forms of the two actuators are identical, and the faults between the actuator 1 and the actuator 2 cannot be distinguished; also, this problem exists between the actuator 3 and the actuator 4. Therefore, for the special case of the aircraft related to the present simulation, faults between the actuator 1 and the actuator 2 and faults between the actuator 3 and the actuator 4 are not isolated, and the designed volume kalman filter set also only comprises 6 sub-filters, which respectively correspond to: actuators 1, 2 fail, actuators 3, 4 fail, actuator 5 fail, actuator 6 fail, actuator 7 fail, and actuator 8 fail.
The total filter failure detection result is shown in fig. 3. It can be seen from the figure that the chi-square test value is in steady state within the first 10 seconds of failure, and does not exceed the set threshold, meaning that no failure has occurred. And starting from 10.02 seconds, the test value starts to exceed the threshold value and remains stable at a later time, which means that there is a case where the actuator fails at about 10 seconds, and the failure is successfully detected.
The sub-filter bank fault isolation results are shown in fig. 4. As is evident from fig. 4, the test values of the other sub-filters, except for sub-filter 1, all had significantly exceeded the threshold and stabilized after 10.02 seconds, which means that either actuator 1 or 2 failed, while the other actuators were normal and the fault was successfully isolated.
The results of the moment-level fault reconstruction are shown in fig. 5 and 6. As can be seen from fig. 5, the reconstructed fault curve keeps track of the actual fault and remains within a small range all the time before 10 seconds, whereas after a fault has occurred, the reconstructed fault curve keeps track of the actual fault values again and remains stable at a time of approximately 0.5 seconds. As can be seen from fig. 6, the reconstruction fault error remains within a small range at all times, which means that the observer reconstruction fault accuracy is high.
The results of the fault reconstruction of the actuator hierarchy are shown in fig. 7. As can be seen from fig. 7, the reconstructed curve tracks the actual failure curve to settle around 0 before the failure occurs, whereas when the failure occurs, the reconstructed curve tracks the actual failure curve very quickly and settles around 0.5.
In summary, most aircraft currently have multiple attitude control system actuators, and these actuators are coupled to each other when providing torque, and accurate fault diagnosis can be achieved only if such coupling relationships are fully considered during diagnosis. The method comprises the steps of establishing an aircraft attitude dynamics model comprising actuator faults and interference, establishing a total state space equation without faults and discretizing, then expanding the state quantity of each actuator to a state vector to obtain an expanded state space equation, designing a multi-model volume Kalman filter bank, carrying out multi-sample chi-square test based on an innovation sequence generated by the filter bank, realizing fault detection and fault isolation according to test results, designing a consistent convergence fault observer to reconstruct moment level faults, finally designing an objective function according to fault isolation information and the moment level faults obtained by reconstruction, and reconstructing the actuator level faults by optimizing the function. The method can accurately detect and isolate the actuator faults in a short time, and can reconstruct the faults in a moment level and an actuator level, thereby laying a foundation for realizing fault recovery more conveniently.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (10)
1. A method of fault diagnosis for an aircraft attitude control system actuator, comprising:
establishing an aircraft attitude dynamics model;
designing a multi-model volume Kalman filter bank according to an aircraft attitude dynamics model;
judging whether an abnormal condition exists in the innovation sequence based on a multi-sample Kalman detection method according to the innovation sequence generated by the multi-model volume Kalman filter bank;
if the innovation sequence is judged to be in an abnormal condition based on the multi-sample chi-square test method, judging that the actuator of the attitude system of the aircraft has a fault, and carrying out fault isolation on the fault;
and designing a consistent convergence fault observer reconstruction moment level fault D according to the fault isolation and aircraft attitude dynamics model, and completing the fault reconstruction of the actuator level.
2. The fault diagnosis method for the aircraft attitude control system actuator according to claim 1, wherein the building of the aircraft attitude dynamics model is as follows:
wherein ω represents the attitude angular velocity of the aircraft, J is the aircraft inertia matrix, u d Triaxial moment accepted by the aircraft, D represents comprehensive faults accepted by the aircraft;
comprehensive fault d=j to which the aircraft is subjected -1 d+u f ；
Wherein u is f The moment level fault is suffered by the aircraft, and d is the external interference suffered by the aircraft.
3. The method for diagnosing faults of an aircraft attitude control system actuator according to claim 1, wherein a fault-free state space equation is established according to an aircraft attitude dynamics model, and discretization processing is performed on the fault-free state space equation to obtain a discrete total state space equation;
the output quantity of the actuator is amplified to a discrete total state space equation to obtain an amplified state space equation;
a multi-model volume Kalman filter bank is designed based on the discrete total state space equation and the augmented state space equation.
4. The fault diagnosis method for an actuator of an aircraft attitude control system according to claim 1, wherein the innovation sequences generated according to the multi-model volume kalman filter bank are m+1 groups, wherein m is the number of the actuators, and the innovation sequences are specifically expressed as follows:
wherein,new information representing the total filter at time k, < ->Represents the measurement vector estimate at the kth moment of the total filter, for>Innovation indicating sub-filter i at time k, < ->Representing the measurement vector estimate at the kth time of the sub-filter i.
5. The method for diagnosing faults of an aircraft attitude control system actuator according to claim 1, wherein the step of judging whether an abnormal condition exists in a new information sequence based on a multi-sample chi-square test method is to construct a new informationBased on the new information->Constructing the statistics obtained->Judging whether the new information sequence has abnormal conditions or not;
if statistics areLess than the set threshold, the new information sequenceNo abnormal situation exists in the column;
if statistics areIf the value is larger than the set threshold value, the information sequence has abnormal conditions.
6. The method of claim 5, wherein the new innovation is:
wherein,representing the j new innovation, N representing the length of a multi-sample inspection window;
the new information is based onConstructing the obtained statistics:
wherein,representing new innovation->Covariance matrix of>Representing new information->The covariance matrix is calculated in the filtering process.
7. The method for diagnosing faults of an aircraft attitude control system actuator according to claim 1, wherein if the multi-sample chi-square test method judges that the innovation sequence is abnormal, then the aircraft attitude system actuator is judged to have faults, and then:
judging the new information in the new information sequenceWhether or not there is an abnormality;
if new is aboutAnd if no abnormality exists, judging that the ith actuator fails, and completing fault isolation.
8. The method for diagnosing faults of an aircraft attitude control system according to claim 1, wherein the fault reconstruction of the aircraft level is completed by designing a consistent converging fault observer reconstruction moment level fault D, designing an objective function and optimizing the objective function according to fault isolation and an aircraft attitude dynamics model.
9. The method for diagnosing faults of an aircraft attitude control system actuator according to claim 8, wherein the specific expression form of the objective function is as follows:
wherein, lambda n (r) represents the matrix I m×m The n-th diagonal term of (a) is replaced by r to obtain a matrix, n represents the n-th actuator fault, Q 1 ∈R 3×3 Representing a matrix of weight coefficients.
10. The method for diagnosing faults of the aircraft attitude control system according to claim 1, wherein the method for detecting the presence of abnormal conditions based on the multi-sample chi-square method is characterized in that if the method for detecting the presence of abnormal conditions based on the multi-sample chi-square method is used for judging that the information sequence is abnormal, all the actuators are judged to be normal, fault isolation and fault reconstruction are not needed, and fault diagnosis is directly finished.
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