CN111538316A - Performance-based fault diagnosis method and system for actuating mechanism of closed-loop control system - Google Patents
Performance-based fault diagnosis method and system for actuating mechanism of closed-loop control system Download PDFInfo
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Abstract
The invention discloses a performance-based fault diagnosis method and system for an actuating mechanism of a closed-loop control system. The method comprises the following steps: establishing a linear nominal model of the control system under the condition of no fault, and determining an identification model of the actual control system according to input data and output data of the actual control system; determining a first time domain performance residual error according to a difference value between the output of the linear nominal model under the closed-loop feedback and the output of the identification model under the closed-loop feedback; determining a first frequency domain performance residual error and a first stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the identification model; and carrying out fault detection according to the time domain performance residual error, the frequency domain performance residual error and the stable domain performance residual error between the linear nominal model and the identification model. By adopting the method and the system, the fault diagnosis is carried out by establishing the relation between the fault of the actuating mechanism and the performance change of the control system after the closed loop, so that the reliability and the applicability of the fault diagnosis of the control system are improved.
Description
Technical Field
The invention relates to the technical field of fault diagnosis, in particular to a performance-based fault diagnosis method and system for an actuating mechanism of a closed-loop control system.
Background
The traditional fault diagnosis method is generally based on a hardware redundancy system, and a voting strategy is adopted for diagnosis, and the main problems of the hardware redundancy are that the maintenance cost of equipment is high, and extra installation space is required. To solve this problem, a diagnostic scheme for resolving redundancy is proposed, in which a residual signal is generated by a multi-signal consistency check technique, and a method for determining a fault of a system by analyzing the residual, i.e., a model-based fault diagnosis method. Common Fault Detection and Isolation (FDI) methods based on models mainly include an observer method, a parity method, and a parameter estimation method.
In the existing fault diagnosis technology, most of the fault diagnosis is carried out on an open-loop system, and the influence of a closed loop of a control system on the fault diagnosis performance is not considered. In addition, most diagnostic methods assume that the fault in the system is an additive fault, which has certain limitations. However, for the closed-loop feedback control system, because the closed-loop control system has certain robustness and fault tolerance capability, namely is insensitive to the change (additive or multiplicative change) of the system, the closed-loop feedback control system has a wider stable working area. Therefore, the existing diagnosis method for diagnosing the fault by using the open-loop information cannot measure the influence on the performance of the closed-loop feedback control system after the fault occurs. If the influence of the fault on the performance of the closed-loop system cannot be known, the fault decision and fault-tolerant control of the system can be adversely affected. For example, in some feedback control systems, despite minor actuator failure, there is a significant hazard from a system closed loop performance perspective. Similarly, in some cases, although the actuator has a fault that appears to be serious (for example, the fault of the actuator changes the open-loop system from a stable system to an unstable system), under the correction action of the feedback controller itself, the influence of the fault is weakened and suppressed, and even the closed-loop performance of the system is not significantly degraded, in this case, from the viewpoint of safe operation, the closed-loop control system does not need to take measures of error control such as control law reconfiguration, thereby avoiding some risks caused by unnecessary error-tolerant switching control. Therefore, it is necessary to perform fault diagnosis from an index on the level of functionality of the closed-loop control system.
Disclosure of Invention
The invention aims to provide a performance-based fault diagnosis method and system for an execution mechanism of a closed-loop control system, which are used for carrying out fault diagnosis by establishing a relation between the fault of the execution mechanism and the performance change of the closed-loop control system, so that the reliability and the practicability of the fault diagnosis of the control system are improved.
In order to achieve the purpose, the invention provides the following scheme:
a performance-based fault diagnosis method for an actuator of a closed-loop control system comprises the following steps:
acquiring input data and output data of an actual control system;
establishing a linear nominal model of a control system model under the condition of no fault according to the working principle of the control system;
determining an identification model of the actual control system according to the input data and the output data of the actual control system;
acquiring instruction input data;
calculating the output of the linear nominal model under closed-loop feedback according to the instruction input data, and calculating the output of the identification model under closed-loop feedback according to the instruction input data;
determining a first time domain performance residual error according to a difference value between the output of the linear nominal model under closed-loop feedback and the output of the identification model under closed-loop feedback; the first time domain performance residual error is a time domain performance residual error between the linear nominal model and the identification model;
determining a first frequency domain performance residual error and a first stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the identification model; the first frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the identification model, and the first stable domain performance residual is a stable domain performance residual between the linear nominal model and the identification model;
and carrying out fault detection according to the first time domain performance residual error, the first frequency domain performance residual error and the first stable domain performance residual error.
Optionally, the performing fault detection according to the first time domain performance residual, the first frequency domain performance residual and the first stable domain performance residual specifically includes:
respectively carrying out normalization processing on the first time domain performance residual error, the first frequency domain performance residual error and the first stable domain performance residual error;
forming points in a three-dimensional composite performance residual error space by the normalized first time domain performance residual error, the normalized first frequency domain performance residual error and the normalized first stable domain performance residual error; the coordinate system of the three-dimensional composite performance residual error space takes a time domain performance residual error as an x axis, a frequency domain performance residual error as a y axis and a stable domain performance residual error as a z axis, and points in the coordinate system and an origin point form a composite performance residual error vector;
judging the size of the composite performance residual vector length and a preset fault threshold value; if the length of the composite performance residual error vector is smaller than a preset fault threshold value, the actual control system executing mechanism does not have a fault; otherwise, the actual control system executing mechanism is in failure.
Optionally, after the performing fault detection according to the first time domain performance residual, the first frequency domain performance residual, and the first stable domain performance residual, the method further includes:
acquiring characterization parameters of different fault modes; the characterization parameter is a parameter representing a fault;
respectively establishing linear fault models of the control system model under the fault condition according to the characterization parameters of different fault modes;
calculating the output of the linear fault model under closed-loop feedback according to the instruction input data;
determining a second time domain performance residual error according to a difference value between the output of the linear nominal model under closed-loop feedback and the output of the linear fault model under closed-loop feedback; the second time domain performance residual error is a time domain performance residual error between the linear nominal model and the linear fault model;
determining a second frequency domain performance residual error and a second stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the linear fault model; the second frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the linear fault model, and the second stable domain performance residual is a stable domain performance residual between the linear nominal model and the linear fault model;
and judging the fault type and the fault degree according to the second time domain performance residual error, the second frequency domain performance residual error and the second stable domain performance residual error.
Optionally, the determining the fault type and the fault degree according to the second time domain performance residual, the second frequency domain performance residual and the second stable domain performance residual specifically includes:
respectively normalizing the second time domain performance residual error, the second frequency domain performance residual error and the second stable domain performance residual error aiming at each fault type;
establishing an executing mechanism fault space library according to the normalized second time domain performance residual error, the normalized second frequency domain performance residual error and the normalized second stable domain performance residual error of each fault type;
and judging the fault type and the fault size in the executing mechanism fault space library according to the direction of the composite performance residual error vector.
The invention also provides a performance-based fault diagnosis system for the actuating mechanism of the closed-loop control system, which comprises the following components:
the actual control system data acquisition module is used for acquiring input data and output data of an actual control system;
the linear nominal model establishing module is used for establishing a linear nominal model of the control system model under the fault-free condition according to the working principle of the control system;
the identification model establishing module is used for determining an identification model of the actual control system according to the input data and the output data of the actual control system;
the instruction input data acquisition module is used for acquiring instruction input data;
the first output calculation module is used for calculating the output of the linear nominal model under closed-loop feedback according to the instruction input data and calculating the output of the identification model under closed-loop feedback according to the instruction input data;
the first time domain performance residual error determining module is used for determining a first time domain performance residual error according to a difference value between the output of the linear nominal model under the closed-loop feedback and the output of the identification model under the closed-loop feedback; the first time domain performance residual error is a time domain performance residual error between the linear nominal model and the identification model;
a first gap measurement calculation module, configured to determine a first frequency domain performance residual and a first stable domain performance residual by using a gap measurement method according to the linear nominal model and the identification model; the first frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the identification model, and the first stable domain performance residual is a stable domain performance residual between the linear nominal model and the identification model;
and the fault detection module is used for carrying out fault diagnosis according to the first time domain performance residual error, the first frequency domain performance residual error and the first stable domain performance residual error.
Optionally, the fault detection module specifically includes:
a first normalization processing unit, configured to perform normalization processing on the first time-domain performance residual, the first frequency-domain performance residual, and the first stable-domain performance residual, respectively;
a composite performance residual vector generating unit, configured to form the normalized first time domain performance residual, the normalized first frequency domain performance residual, and the normalized first stable domain performance residual into a point in a three-dimensional composite performance residual space; the coordinate system of the three-dimensional composite performance residual error space takes a time domain performance residual error as an x axis, a frequency domain performance residual error as a y axis and a stable domain performance residual error as a z axis, and points in the coordinate system and an origin point form a composite performance residual error vector;
the fault detection unit is used for judging the size of the composite performance residual error vector length and a preset fault threshold value; if the length of the composite performance residual error vector is smaller than a preset fault threshold value, the actual control system executing mechanism does not have a fault; otherwise, the actual control system executing mechanism is in failure.
Optionally, the system for diagnosing fault of actuator of closed-loop control system further includes:
the characterization parameter acquisition module is used for acquiring characterization parameters of different fault modes; the characterization parameter is a parameter representing a fault;
the linear fault model establishing module is used for respectively establishing linear fault models of the control system model under the fault condition according to the characterization parameters of different fault modes;
the second output calculation module is used for calculating the output of the linear fault model under closed-loop feedback according to the instruction input data;
the second time domain performance residual error module is used for determining a second time domain performance residual error according to the difference value of the output of the linear nominal model under the closed-loop feedback and the output of the linear fault model under the closed-loop feedback; the second time domain performance residual error is a time domain performance residual error between the linear nominal model and the linear fault model;
the second gap measurement calculation module is used for determining a second frequency domain performance residual error and a second stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the linear fault model; the second frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the linear fault model, and the second stable domain performance residual is a stable domain performance residual between the linear nominal model and the linear fault model;
and the fault diagnosis module is used for judging the fault type and the fault degree according to the second time domain performance residual error, the second frequency domain performance residual error and the second stable domain performance residual error.
Optionally, the fault diagnosis module specifically includes:
a second normalization processing unit, configured to, for each fault type, perform normalization processing on the second time-domain performance residual, the second frequency-domain performance residual, and the second stable-domain performance residual, respectively;
the executing mechanism fault space library establishing unit is used for establishing an executing mechanism fault space library according to the normalized second time domain performance residual error, the normalized second frequency domain performance residual error and the normalized second stable domain performance residual error of each fault type;
and the fault type judging unit is used for judging the fault type and the fault size in the executing mechanism fault space library according to the direction of the composite performance residual error vector.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a performance-based fault diagnosis method and system for an actuating mechanism of a closed-loop control system, which are characterized in that time domain performance residual errors, frequency domain performance residual errors and stability domain performance residual errors between a nominal model and an identification model are determined according to the identification model of an actual control system and the nominal model of a control system model; the fault diagnosis is carried out by establishing the relation between the fault of the actuating mechanism and the performance of the system after the closed loop, so that the reliability and the practicability of the fault diagnosis are improved.
In addition, the invention constructs a composite performance residual vector based on multi-domain (time domain, frequency domain and stable domain) information, the vector information can comprehensively evaluate the difference between the stability, the rapidity and the accuracy of the actual closed-loop control system and a nominal model after additive and multiplicative faults occur from the performance level of the actual control system, and the length information and the direction information of the residual vector are utilized to respectively carry out fault diagnosis and fault identification, thereby avoiding the defect of single-domain or less-domain information in the aspect of fault diagnosis of the control system.
The invention also introduces the gap measurement thought in robust control into the field of fault diagnosis as a quantitative basis of the rapidity residual and the stability residual of the closed-loop control system to be diagnosed, and the performance residual based on the gap measurement quantitatively associates the fault of the control system execution mechanism with the performance of the closed-loop system, thereby effectively evaluating the closed-loop hazard degree of the fault and providing a theoretical basis for the decision of the fault-tolerant control of the control system execution mechanism.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart of a method for diagnosing faults of an actuator of a performance-based closed-loop control system in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of fault diagnosis based on multi-domain composite performance residuals according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a time domain-frequency domain-stable domain composite performance residual vector space in an embodiment of the present invention;
FIG. 4 is a block diagram of a performance based fault diagnostic system for an actuator of a closed loop control system in accordance with an embodiment of the present invention;
FIG. 5 is a schematic diagram of a closed-loop control system of an electro-hydraulic actuator according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating a simulation result of diagnosing a fault of an electro-hydraulic servo valve according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating a residual vector diagram of the electro-hydraulic servo valve performance in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a performance-based fault diagnosis method and system for an execution mechanism of a closed-loop control system, which are used for carrying out fault diagnosis by establishing a relation between the fault of the execution mechanism and the performance change of the closed-loop control system, so that the reliability and the applicability of the fault diagnosis of the control system are improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention provides a performance-based fault diagnosis method for an execution mechanism of a closed-loop control system, and fig. 1 is a flow chart of the performance-based fault diagnosis method for the execution mechanism of the closed-loop control system in the embodiment of the invention, as shown in fig. 1, the method comprises the following steps:
step 101: input data and output data of an actual control system are acquired.
Step 102: and establishing a linear nominal model of the control system model under the fault-free condition according to the working principle of the control system.
As shown in FIG. 2, an n-order nonlinear nominal model for describing a single-input single-output control system is established
y is h (x, u), where x is the state vector of the control system, and x is [ x ═ x { [1,x2,…,xn]U is the input to the control system and y is the output of the control system.
According to Taylor's expansion theorem, the high-order nonlinear nominal model is processed
At the j operating point
Carrying out model linearization treatment:
in the formula, gj(x, u) represents the rate of change of the state vector of the dynamic system, hj(x, u) represents the output of the dynamic system,
the jth linearized operating point is shown, Δ x represents a slight increment of the state in the vicinity of the jth operating point, and Δ u represents a slight increment of the command in the vicinity of the jth operating point.
Wherein,
Gj(s)＝Cj(sI-Aj)-1Bj+Dj
linear nominal model G by adopting Hankel singular value methodj(s) at the jth operating point
And carrying out model reduction processing. First, the system matrix A is calculated using the following formulajHankel singular value of:
wherein λ iskWhere (k is 1,2, …, n) is the kth characteristic value, Pj，QjControllability and objective glama matrix satisfying the following relationships, respectively:
AjPj+Pj(Aj)T＝-Bj(Bj)T
(Aj)TQj+QjAj＝-(Cj)TCj
hankel singular value sigma obtained according to calculationj|kAnd respectively reserving main singular values to obtain a reduced-order linear nominal model:
step 103: and determining the identification model of the actual control system according to the input data and the output data of the actual control system.
Under the input of a step instruction, acquiring instruction output data of a controller and measurement output data of a sensor in an actual system, then carrying out filtering cleaning pretreatment on the acquired data, and storing the pretreated data for identifying an actuating mechanism open-loop control system model; using least squares, by minimizing the square of the generalized errorDetermining parameters of the system model by the sum function to obtain an identification model of the control system
Step 104: instruction input data is acquired.
Step 105: and calculating the output of the linear nominal model under the closed-loop feedback according to the instruction input data, and calculating the output of the identification model under the closed-loop feedback according to the instruction input data.
Step 106: and determining the time domain performance residual error between the linear nominal model and the identification model according to the difference value of the output of the linear nominal model under the closed-loop feedback and the output of the identification model under the closed-loop feedback.
Calculating a reduced linear nominal model under step command input
Output y under closed loop feedbacknominal(t) calculating an actual operation system identification model
Output y of closed-loop feedback under same command inputfault(t) calculating a time domain performance residual ey：
ey＝yfault(t)-ynominal(t)
Step 107: and determining the frequency domain performance residual error and the stable domain performance residual error between the linear nominal model and the identification model by adopting a gap measurement method according to the linear nominal model and the identification model.
Computing a linear nominal model using a gap metric equation
And identifying the obtained actual model
Frequency domain performance residual betweenν：
When the feedback controller K makes the system G unstable, the stability is defined as an index of 0. When the feedback controller stabilizes the system, the following stability calculation method is defined:
calculating a linear nominal model using the following equation
And identifying the obtained actual model
Steady domain performance residual Δ b betweenK：
Step 108: and carrying out fault detection according to the time domain performance residual error between the linear nominal model and the identification model, the frequency domain performance residual error between the linear nominal model and the identification model and the stable domain performance residual error.
and respectively carrying out normalization processing on the time domain performance residual error between the linear nominal model and the identification model, the frequency domain performance residual error between the linear nominal model and the identification model and the stable domain performance residual error.
And forming points in a three-dimensional composite performance residual error space by using the normalized first time domain performance residual error, the normalized first frequency domain performance residual error and the normalized first stable domain performance residual error. The coordinate system of the three-dimensional composite performance residual error space takes the time domain performance residual error as an x axis, the frequency domain performance residual error as a y axis, the stable domain performance residual error as a z axis, and points in the coordinate system and an origin point form a composite performance residual error vector.
Judging the size of the composite performance residual vector length and a preset fault threshold value; if the length of the composite performance residual error vector is smaller than a preset fault threshold value, controlling the system execution mechanism not to have a fault; otherwise, the control system executing mechanism is in failure.
Three performance residual indexes ey、νAnd Δ bKRespectively carrying out normalization treatment according to the following formula:
in the formula,
esto control the steady-state tolerance of the system, esIs equal to or more than 0, and α is the maximum fault degree factor.
In the formula,tfor controlling frequency domain indexes corresponding to rapidity in systematic health state, the frequency domain indexes are more than or equal to 0tLess than or equal to 1, and β is the maximum fault factor.
In the formula,
as a nominal model
The stability index of (a) is,
as a real model
The stability index of (a) is,
gamma is the maximum failure degree factor.
The three normalized performance index residuals are formed into a normalized composite performance residual vector H as follows:
step 109: and acquiring the characterization parameters of different failure modes. The characterizing parameter is a parameter indicative of a fault.
Step 110: and respectively establishing a linear fault model of the control system model under the fault condition according to the characterization parameters of different fault modes.
And summarizing typical fault modes of the control system actuator by combining the working characteristics of the control system actuator, determining system parameters capable of representing corresponding fault modes based on the obtained high-order linear nominal model to obtain a high-order nonlinear fault model, and performing fault simulation by changing the size of the system parameters representing faults. The difference between the nominal model and the fault model is that the values of parameters capable of representing the fault type in the fault model are in a normal value range and in an abnormal value range.
Further, the working characteristics of the feedback control system actuator are combined to summarize the typical failure mode set SF＝{F1,F2,…,FmFinding system parameters S capable of representing the failure modes in a linear nominal modelρ＝{ρ1,ρ2,…,ρmWhere ρ isi(i ═ 1,2, …, m) represents the ith fault ρiParameters of the affected system changes, and establishing a high-order nonlinear fault model of the dynamic feedback control system
y＝hρAnd (x, u) for controlling the system fault simulation acquisition data.
According to Taylor expansion theorem, the high-order nonlinear fault model is subjected to
Model line of executionPerforming sexual treatment:
wherein,
linear fault model by adopting Hankel singular value method
At the j operating point
And carrying out model reduction processing. First, the following formula is used to calculate
Hankel singular value of:
wherein λ iskWhere (k is 1,2, …, n) is the kth characteristic value,
controllability and objective glama matrix satisfying the following relationships, respectively:
hankel curiosity obtained according to calculationDifference value
And (3) retaining the main singular values to obtain a reduced-order linear fault model:
step 111: and calculating the output of the linear fault model under closed-loop feedback according to the instruction input data.
Step 112: and determining the time domain performance residual error between the linear nominal model and the linear fault model according to the difference value of the output of the linear nominal model under the closed-loop feedback and the output of the linear fault model under the closed-loop feedback.
Step 113: and determining a frequency domain performance residual error and a stable domain performance residual error between the linear nominal model and the linear fault model by adopting a gap measurement method according to the linear nominal model and the linear fault model.
Step 114: and judging the fault type and the fault degree according to the time domain performance residual error between the linear nominal model and the linear fault model, the frequency domain performance residual error between the linear nominal model and the linear fault model and the stable domain performance residual error.
and respectively carrying out normalization processing on time domain performance residual errors between the linear nominal model and the linear fault model, frequency domain performance residual errors between the linear nominal model and the linear fault model and stable domain performance residual errors aiming at each fault type.
And establishing an actuator fault space library according to the time domain performance residual error between the normalized linear nominal model and the linear fault model of each fault type, the frequency domain performance residual error between the normalized linear nominal model and the linear fault model, and the stable domain performance residual error between the normalized linear nominal model and the linear fault model.
And judging the fault type according to the direction of the composite performance residual error vector in the fault space library of the execution mechanism, and judging the fault degree according to the length of the composite performance residual error vector in the fault space library of the execution mechanism. The vector corresponds to a point in the three-dimensional space, and is respectively regarded as xyz coordinates. The direction of a directional connecting line between the healthy origin and the point is the direction of the vector, and the healthy origin is the origin when no fault occurs.
The executing mechanism fault space library is used for simulating all faults which may occur, are different in type and different in degree by means of tests or simulation, and then respectively calculating multi-domain performance residual errors of the corresponding faults. The residual vectors are in different spatial regions in the three-dimensional coordinate system due to the redundant performance of different faults, i.e. have different directivities of the residual vectors. Based on such a fault database established in advance, when a certain fault occurs in the actual system, the residual vector of the fault is calculated, and the direction of the residual vector in the fault database is used for judging what type of fault occurs. The fault space library is a collection of known directions or spatial distributions of a plurality of faults. A time domain-frequency domain-stable domain composite performance residual vector space diagram is shown in fig. 3.
The present invention further provides a performance-based fault diagnosis system for an actuator of a closed-loop control system, and fig. 4 is a structural diagram of a performance-based fault diagnosis system for an actuator of a closed-loop control system according to an embodiment of the present invention, as shown in fig. 4, the system includes:
and an actual control system data acquisition module 201, configured to acquire input data and output data of an actual control system.
And a linear nominal model establishing module 202 for establishing a linear nominal model of the control system model under the fault-free condition according to the working principle of the control system.
And the identification model establishing module 203 is used for determining an identification model of the actual control system according to the input data and the output data of the actual control system.
And the instruction input data acquisition module 204 is used for acquiring instruction input data.
The first output calculation module 205 is configured to calculate an output of the linear nominal model under the closed-loop feedback according to the instruction input data, and calculate an output of the identification model under the closed-loop feedback according to the instruction input data.
A first time domain performance residual determining module 206, configured to determine a time domain performance residual between the linear nominal model and the identification model according to a difference between an output of the linear nominal model under the closed-loop feedback and an output of the identification model under the closed-loop feedback.
And the first gap measurement calculating module 207 is configured to determine a frequency domain performance residual and a stable domain performance residual between the linear nominal model and the identification model by using a gap measurement method according to the linear nominal model and the identification model.
And the fault detection module 208 is configured to perform fault detection according to the time domain performance residual between the linear nominal model and the identification model, the frequency domain performance residual between the linear nominal model and the identification model, and the stable domain performance residual.
The fault detection module 208 specifically includes:
and the first normalization processing unit is used for respectively carrying out normalization processing on the time domain performance residual error between the linear nominal model and the identification model, the frequency domain performance residual error between the linear nominal model and the identification model and the stable domain performance residual error.
And the composite performance residual vector generating unit is used for forming the normalized first time domain performance residual, the normalized first frequency domain performance residual and the normalized first stable domain performance residual into a point in a three-dimensional composite performance residual space. The coordinate system of the three-dimensional composite performance residual error space takes the time domain performance residual error as an x axis, the frequency domain performance residual error as a y axis, the stable domain performance residual error as a z axis, and points in the coordinate system and an origin point form a composite performance residual error vector.
The fault diagnosis unit is used for judging the length of the composite performance residual error vector and the size of a preset fault threshold; if the length of the composite performance residual error vector is smaller than a preset fault threshold value, controlling the system execution mechanism not to have a fault; otherwise, the control system executing mechanism is in failure.
And a characteristic parameter obtaining module 209, configured to obtain characteristic parameters of different failure modes. The characterizing parameter is a parameter indicative of a fault.
And the linear fault model establishing module 210 is configured to respectively establish a linear fault model of the control system model under the fault condition according to the characterization parameters of different fault modes.
And a second output calculation module 211, configured to calculate an output of the linear fault model under closed-loop feedback according to the instruction input data.
And a second time-domain performance residual module 212, configured to determine a time-domain performance residual between the linear nominal model and the linear fault model according to a difference between an output of the linear nominal model under the closed-loop feedback and an output of the linear fault model under the closed-loop feedback.
And a second gap measurement calculating module 213, configured to determine, according to the linear nominal model and the linear fault model, a frequency domain performance residual error and a stable domain performance residual error between the linear nominal model and the linear fault model by using a gap measurement method.
And the fault diagnosis module 214 is configured to perform fault type and fault degree judgment according to the time domain performance residual between the linear nominal model and the linear fault model, the frequency domain performance residual between the linear nominal model and the linear fault model, and the stability domain performance residual.
The fault diagnosis module 214 specifically includes:
and the second normalization processing unit is used for respectively normalizing the time domain performance residual error between the linear nominal model and the linear fault model, the frequency domain performance residual error between the linear nominal model and the linear fault model and the stable domain performance residual error aiming at each fault type.
And the executing mechanism fault space library establishing unit is used for establishing the executing mechanism fault space library according to the time domain performance residual error between the normalized linear nominal model and the linear fault model of each fault type, the frequency domain performance residual error between the normalized linear nominal model and the linear fault model and the stable domain performance residual error between the normalized linear nominal model and the linear fault model.
And the fault type judging unit is used for judging the fault type according to the direction of the composite performance residual error vector in the executing mechanism fault space library and judging the fault degree according to the length of the composite performance residual error vector in the executing mechanism fault space library.
For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The effectiveness of the method is verified through a simulation example by taking an actuating mechanism of a fuel control system of certain aviation equipment as a diagnosis object. The fuel control system mainly comprises an electro-hydraulic servo valve, a metering valve, a differential pressure valve and other elements, wherein the electro-hydraulic servo valve and the metering valve are main components of an actuating mechanism and are shown in figure 5. As the valve core displacement of the electro-hydraulic servo valve is usually very small, the electro-hydraulic servo valve is regarded as working near a zero working point, and a state vector is selected
Where θ is the yaw angle of the servo valve torque motor,
is the angular acceleration of the deflection of the servo valve torque motor, P1Is the pressure in the control chamber on the left side of the spool of the servo valve, P2Is the pressure in the control chamber on the right side of the spool of the servo valve, P3Is the pressure behind the nozzle, and is,
is the speed of the servo spool, xsIs the displacement of the servo spool, and y is the output displacement of the metering valve. Let the control input current of the torque motor be ieThe system supply pressure is Ps。
and 2, combining the characteristics of an actuating mechanism of the fuel control system, wherein the typical failure mode mainly comprises the following steps: the method comprises the following steps of torque motor electromagnetic performance degradation, nozzle pollution blockage faults, pilot-level oil filtration pollution blockage and feedback rod ball head gap abrasion faults.
The system parameters characterizing the failure modes are respectively as follows: current-torque gain coefficient, effective diameter of nozzle, pilot stage control pressure and size of ball head gap of feedback rod. And simulating the degree of different faults by changing the parameters in the simulation model, thereby obtaining the nonlinear fault model after the faults.
Step 3, carrying out model linearization on the 8-order nonlinear nominal model obtained in the step 1 at a zero working point, wherein the result is as follows:
B0＝[1.1×1060 0 0 0 0 0 0]T
C0＝[0 0 0 0 0 0 0 1]，u＝ie
in the above formula, A0、B0、C0Is a system matrix, A0、B0、C0Is Aj、Bj、CjIn the case when j is 0, it is the result of the linearization at the zero operating point, and u is the input to the system.
Reducing the order of the model by adopting a Hankel singular value method, writing the reduced order into a transfer function form, and obtaining a simplified open-loop nominal model of the fuel metering system:
and 4, respectively injecting the four types of faults into the high-order nonlinear model by adopting a simulation means, and obtaining results as shown in fig. 6(a) - (d), wherein fig. 6(a) is an electromagnetic performance degradation simulation result diagram, fig. 6(b) is a nozzle pollution blockage simulation result diagram, fig. 6(c) is a pilot oil filter blockage simulation result diagram, and fig. 6(d) is a ball head gap wear simulation result diagram. The input and output data of the system are collected and the system model is identified, and the result is shown in table 1.
TABLE 1 electrohydraulic servo control system failure and corresponding model identification
Step 5, residual error generation: calculating the performance residual error of the time domain index according to the linear nominal model obtained in the step 3 and the system output information measured in the step 4; and (4) calculating the frequency domain performance residual error and the stable domain performance residual error between the simplified linear nominal model obtained in the step (3) and the actual model obtained in the step (4) according to a formula, wherein the calculation result is shown in a table 2.
TABLE 2 Multi-domain performance residual error of electro-hydraulic servo control system under different failure modes
And step 6, respectively determining maximum fault degree factors alpha, beta and gamma corresponding to time domain performance, frequency domain performance and stability domain performance according to control requirement indexes of the fuel metering control system, and further performing normalization processing on the three performance residual errors obtained in the step 5 to obtain composite performance residual error vectors under different faults, wherein the composite performance residual error vectors are shown in a table 3.
According to the control quality requirement of a certain fuel control system, the steady state error is less than or equal to 0.05mm, and the rise time is less than or equal to 0.04s (corresponding to
) The stability margin is less than or equal to 45 degrees (corresponding to
). The steady state error was set to 0.2mm and the rise time was set to 0.1s (corresponding toν0.3336), the stable domain residual error is 0.8375, which corresponds to the most serious performance index, α is 2, β is 0.4, and γ is 0.7.
TABLE 3 normalized Standard Multi-Domain Performance residual
And 7, performing typical fault simulation on each working point of the executing mechanism by an experiment or simulation means, and repeatedly adopting the methods in the steps 5 and 6 to obtain residual vectors under different faults so as to form a fault space library of the executing mechanism of the dynamic feedback control system.
And 8, setting fault thresholds of the three performance residual error components according to the performance requirements of the control system. And (4) carrying out fault diagnosis by using the length of the composite performance residual vector obtained in the step (6), and carrying out fault isolation by using the direction of the composite performance residual vector and the fault space obtained in the step (7). As shown in fig. 7, the residual vectors of the four faults injected in this embodiment are:
H1＝[0.0000 0.3318 0.0000]T
H2＝[-1.0000 0.0001 0.0010]T
H3＝[0.0000 0.2359 0.2381]T
H4＝[-1.0000 0.8708 1.0000]T。
wherein H1Residual vector of electromagnetic performance degradation fault, H2Residual vector of nozzle contamination plugging failure, H3Residual vector, H, for leading oil filter plugging fault4And the residual vector of the ball head clearance abrasion fault is obtained.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In summary, this summary should not be construed to limit the present invention.
Claims (8)
1. A performance-based fault diagnosis method for an actuating mechanism of a closed-loop control system is characterized by comprising the following steps:
acquiring input data and output data of an actual control system;
establishing a linear nominal model of a control system model under the condition of no fault according to the working principle of the control system;
determining an identification model of the actual control system according to the input data and the output data of the actual control system;
acquiring instruction input data;
calculating the output of the linear nominal model under closed-loop feedback according to the instruction input data, and calculating the output of the identification model under closed-loop feedback according to the instruction input data;
determining a first time domain performance residual error according to a difference value between the output of the linear nominal model under closed-loop feedback and the output of the identification model under closed-loop feedback; the first time domain performance residual error is a time domain performance residual error between the linear nominal model and the identification model;
determining a first frequency domain performance residual error and a first stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the identification model; the first frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the identification model, and the first stable domain performance residual is a stable domain performance residual between the linear nominal model and the identification model;
and carrying out fault detection according to the first time domain performance residual error, the first frequency domain performance residual error and the first stable domain performance residual error.
2. The method of claim 1, wherein the performing fault detection based on the first time domain performance residual, the first frequency domain performance residual, and the first stability domain performance residual comprises:
respectively carrying out normalization processing on the first time domain performance residual error, the first frequency domain performance residual error and the first stable domain performance residual error;
forming points in a three-dimensional composite performance residual error space by the normalized first time domain performance residual error, the normalized first frequency domain performance residual error and the normalized first stable domain performance residual error; the coordinate system of the three-dimensional composite performance residual error space takes a time domain performance residual error as an x axis, a frequency domain performance residual error as a y axis and a stable domain performance residual error as a z axis, and points in the coordinate system and an origin point form a composite performance residual error vector;
judging the size of the composite performance residual vector length and a preset fault threshold value; if the length of the composite performance residual error vector is smaller than a preset fault threshold value, the actual control system executing mechanism does not have a fault; otherwise, the actual control system executing mechanism is in failure.
3. The method of claim 2, wherein the performing fault detection based on the first time domain performance residual, the first frequency domain performance residual, and the first stability domain performance residual further comprises:
acquiring characterization parameters of different fault modes; the characterization parameter is a parameter representing a fault;
respectively establishing linear fault models of the control system model under the fault condition according to the characterization parameters of different fault modes;
calculating the output of the linear fault model under closed-loop feedback according to the instruction input data;
determining a second time domain performance residual error according to a difference value between the output of the linear nominal model under closed-loop feedback and the output of the linear fault model under closed-loop feedback; the second time domain performance residual error is a time domain performance residual error between the linear nominal model and the linear fault model;
determining a second frequency domain performance residual error and a second stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the linear fault model; the second frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the linear fault model, and the second stable domain performance residual is a stable domain performance residual between the linear nominal model and the linear fault model;
and judging the fault type and the fault degree according to the second time domain performance residual error, the second frequency domain performance residual error and the second stable domain performance residual error.
4. The method for diagnosing faults of an actuator of a performance-based closed-loop control system according to claim 3, wherein the determining of the fault type and the fault degree according to the second time-domain performance residual, the second frequency-domain performance residual and the second stable-domain performance residual specifically comprises:
respectively normalizing the second time domain performance residual error, the second frequency domain performance residual error and the second stable domain performance residual error aiming at each fault type;
establishing an executing mechanism fault space library according to the normalized second time domain performance residual error, the normalized second frequency domain performance residual error and the normalized second stable domain performance residual error of each fault type;
and judging the fault type and the fault size in the executing mechanism fault space library according to the direction of the composite performance residual error vector.
5. A performance-based closed loop control system actuator fault diagnostic system, comprising:
the actual control system data acquisition module is used for acquiring input data and output data of an actual control system;
the linear nominal model establishing module is used for establishing a linear nominal model of the control system model under the fault-free condition according to the working principle of the control system;
the identification model establishing module is used for determining an identification model of the actual control system according to the input data and the output data of the actual control system;
the instruction input data acquisition module is used for acquiring instruction input data;
the first output calculation module is used for calculating the output of the linear nominal model under closed-loop feedback according to the instruction input data and calculating the output of the identification model under closed-loop feedback according to the instruction input data;
the first time domain performance residual error determining module is used for determining a first time domain performance residual error according to a difference value between the output of the linear nominal model under the closed-loop feedback and the output of the identification model under the closed-loop feedback; the first time domain performance residual error is a time domain performance residual error between the linear nominal model and the identification model;
a first gap measurement calculation module, configured to determine a first frequency domain performance residual and a first stable domain performance residual by using a gap measurement method according to the linear nominal model and the identification model; the first frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the identification model, and the first stable domain performance residual is a stable domain performance residual between the linear nominal model and the identification model;
and the fault detection module is used for carrying out fault detection according to the first time domain performance residual error, the first frequency domain performance residual error and the first stable domain performance residual error.
6. The system of claim 5, wherein the fault detection module comprises:
a first normalization processing unit, configured to perform normalization processing on the first time-domain performance residual, the first frequency-domain performance residual, and the first stable-domain performance residual, respectively;
a composite performance residual vector generating unit, configured to form the normalized first time domain performance residual, the normalized first frequency domain performance residual, and the normalized first stable domain performance residual into a point in a three-dimensional composite performance residual space; the coordinate system of the three-dimensional composite performance residual error space takes a time domain performance residual error as an x axis, a frequency domain performance residual error as a y axis and a stable domain performance residual error as a z axis, and points in the coordinate system and an origin point form a composite performance residual error vector;
the fault detection unit is used for judging the size of the composite performance residual error vector length and a preset fault threshold value; if the length of the composite performance residual error vector is smaller than a preset fault threshold value, the actual control system executing mechanism does not have a fault; otherwise, the actual control system executing mechanism is in failure.
7. The closed-loop control system actuator fault diagnostic system of claim 6, wherein the closed-loop control system actuator fault diagnostic system further comprises:
the characterization parameter acquisition module is used for acquiring characterization parameters of different fault modes; the characterization parameter is a parameter representing a fault;
the linear fault model establishing module is used for respectively establishing linear fault models of the control system model under the fault condition according to the characterization parameters of different fault modes;
the second output calculation module is used for calculating the output of the linear fault model under closed-loop feedback according to the instruction input data;
the second time domain performance residual error module is used for determining a second time domain performance residual error according to the difference value of the output of the linear nominal model under the closed-loop feedback and the output of the linear fault model under the closed-loop feedback; the second time domain performance residual error is a time domain performance residual error between the linear nominal model and the linear fault model;
the second gap measurement calculation module is used for determining a second frequency domain performance residual error and a second stable domain performance residual error by adopting a gap measurement method according to the linear nominal model and the linear fault model; the second frequency domain performance residual is a frequency domain performance residual between the linear nominal model and the linear fault model, and the second stable domain performance residual is a stable domain performance residual between the linear nominal model and the linear fault model;
and the fault diagnosis module is used for judging the fault type and the fault degree according to the second time domain performance residual error, the second frequency domain performance residual error and the second stable domain performance residual error.
8. The system of claim 7, wherein the fault diagnosis module comprises:
a second normalization processing unit, configured to, for each fault type, perform normalization processing on the second time-domain performance residual, the second frequency-domain performance residual, and the second stable-domain performance residual, respectively;
the executing mechanism fault space library establishing unit is used for establishing an executing mechanism fault space library according to the normalized second time domain performance residual error, the normalized second frequency domain performance residual error and the normalized second stable domain performance residual error of each fault type;
and the fault type judging unit is used for judging the fault type and the fault size in the executing mechanism fault space library according to the direction of the composite performance residual error vector.
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