CN114237199B - Aeroengine execution loop fault detection method based on adaptive comparator - Google Patents
Aeroengine execution loop fault detection method based on adaptive comparator Download PDFInfo
- Publication number
- CN114237199B CN114237199B CN202111432839.9A CN202111432839A CN114237199B CN 114237199 B CN114237199 B CN 114237199B CN 202111432839 A CN202111432839 A CN 202111432839A CN 114237199 B CN114237199 B CN 114237199B
- Authority
- CN
- China
- Prior art keywords
- fault detection
- value
- execution loop
- execution
- threshold
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 56
- 230000003044 adaptive effect Effects 0.000 title claims abstract description 25
- 238000001914 filtration Methods 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 32
- 239000000446 fuel Substances 0.000 claims description 26
- 238000006073 displacement reaction Methods 0.000 claims description 22
- 230000007246 mechanism Effects 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 12
- 238000012546 transfer Methods 0.000 claims description 8
- 238000013016 damping Methods 0.000 claims description 3
- 230000010354 integration Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 description 10
- 239000003921 oil Substances 0.000 description 10
- 238000003745 diagnosis Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 5
- 238000012360 testing method Methods 0.000 description 5
- 230000007704 transition Effects 0.000 description 5
- 238000004088 simulation Methods 0.000 description 3
- 239000007921 spray Substances 0.000 description 3
- 230000004044 response Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000295 fuel oil Substances 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
- Feedback Control In General (AREA)
Abstract
The application discloses an aeroengine execution loop fault detection method based on an adaptive comparator, which comprises the following steps: determining an execution loop and an execution loop model in the aero-engine, and constructing a fault detection model according to the execution loop model; determining a first threshold for fault detection in a steady state condition; filtering according to the acquired control output current value to obtain a filtered current value, fitting to obtain a first reference table, and inquiring the first reference table to obtain a second threshold value corresponding to the filtered current value under the control current value; fitting to obtain a second reference table, and inquiring the second reference table to obtain a third threshold value corresponding to the control current value; constructing a relation between a first threshold, a second threshold, a third threshold and the self-adaptive residual; and comparing the relation between the absolute value of the difference between the feedback value of the execution loop and the output value of the fault detection model and the self-adaptive residual error threshold, and when the relation is greater than or equal to zero and reaches a plurality of periods, the execution loop fails, otherwise, the execution loop does not fail.
Description
Technical Field
The application belongs to the technical field of aeroengine fault detection, and particularly relates to an aeroengine execution loop fault detection method based on a self-adaptive comparator.
Background
The aeroengine execution loop is used for accurately tracking, compensating the external interference, the nonlinear influence of the execution mechanism and the controlled object, obtaining faster response of the closed loop system and realizing steady-state and dynamic performance requirements of the execution loop. The control system has complex execution loop, faults of each link can influence the performance of the closed loop system, and the working reliability of the control system is critical to the safety of an engine, so that the fault detection technology of the execution loop is necessary. At present, an aeroengine generally only monitors control deviation and control variable, and an actuator soft fault is usually compensated by a PID controller, wherein the control deviation approaches to 0, and if only the control deviation and the control variable are monitored, the soft fault or smaller sensor deviation hard fault cannot be detected.
The signal-based fault diagnosis of the execution loop of the aeroengine generally sets a maximum value and a minimum value of the controlled variable and a first derivative of the controlled variable in advance respectively, and also adopts a method for comparing a planned value and a feedback value of the controlled variable of the execution loop to detect faults. If the controlled variable, or its derivative, or the deviation of the planned value from the feedback value exceeds a threshold range, a failure of the servo loop is indicated. Although the judging principle of the method is simple and easy to realize, the method has better diagnosis result on hard faults, the probability of false alarm exists on soft faults, and the probability of false alarm exists on normal fluctuation of some controlled variables.
In another fault diagnosis method based on a model, a first-order inertia link is generally used as a model for diagnosis, and the model output is compared with a controlled variable of a real execution loop. Because the actuating mechanism comprises a nonlinear link, the control energy output by the controller has a constraint function, the position and the speed of the actuating mechanism have saturation problems, in order to achieve both transition state and steady state, the fault detection time is required to be prolonged, meanwhile, the fault detection threshold range is set to be very large, the problem of overlong detection time exists, and a certain alarm leakage rate exists, so that the real-time performance and the accuracy of fault detection are affected.
Disclosure of Invention
The application aims to provide an aeroengine execution loop fault detection method based on an adaptive comparator, which solves or reduces at least one problem in the background art.
The technical scheme of the application is as follows: an aeroengine execution loop fault detection method based on an adaptive comparator, the execution loop fault detection method comprising:
determining an execution loop and an execution loop model in the aero-engine, and constructing a fault detection model according to the execution loop model;
determining a first threshold for fault detection in a steady state condition;
filtering according to the acquired control current value to obtain a filtered current value, fitting the filtered current value to obtain a first reference table of the relation between a second threshold value and the filtered current value, and inquiring the first reference table to obtain a second threshold value corresponding to the filtered current value under the control current value;
fitting the control current value to obtain a second reference table of the relation between a third threshold value and the control current value, and inquiring the second reference table to obtain a third threshold value corresponding to the control current value;
constructing a relation between a first threshold, a second threshold, a third threshold and the self-adaptive residual;
and comparing the relation between the absolute value of the difference between the feedback value of the execution loop and the output value of the fault detection model and the self-adaptive residual error threshold, and when the relation is greater than or equal to zero and reaches a plurality of periods, the execution loop fails, otherwise, the execution loop does not fail.
Further, the execution loop in the aero-engine comprises a main fuel metering execution loop, a boost fuel metering execution loop, an angle execution loop and a nozzle area execution loop.
Further, the process of constructing the fault detection model according to the execution loop model includes:
according to the displacement plan value of the execution loop and the displacement output value of the fault detection model, a deviation amount e is obtained;
constructing a relation between the output current I of the controller and the balance current I_BAL in the actuating mechanism;
subtracting the expected balance current I_BAL from the controller output current I to obtain the input current of the servo valve;
adopting a second-order link to approximately represent a transfer function model of the servo valve, adopting a mathematical prototype to equivalently execute a valve in a loop by using an integrator, adopting a delay function to simulate a driving force process and a flow establishing process, obtaining a flow difference of the electrohydraulic servo valve after the equivalent second-order transfer function of the servo valve, performing delay processing of the delay link on the flow to obtain a single-step integral quantity of the displacement of the metering valve, and obtaining the displacement of the metering valve after integration;
and limiting the upper limit and the lower limit of the single-step integral quantity, accumulating the limited single-step integral, and limiting the range of the valve movement travel to finally obtain the airborne fault detection model.
Further, the controller output current I has the following relationship with the balance current i_bal in the actuator:
wherein k is p Is a proportional control coefficient, e is a deviation amount, T i And T D The integral time constant and the differential time constant are respectively, and t is time.
Further, the input current Δi of the servo valve is: Δi=i-i_bal.
Further, the transfer function model of the second-order link is:
where Kac is the loop gain, w is the natural frequency, and ζ is the damping ratio.
Further, the fault detection model is as follows:
in the formula, lm_mdl is a fault detection model, delay_lm is a Delay link, and Δi is a servo valve input current.
Further, the control output current value I and the filter current value i_f satisfy the following:
in the method, in the process of the application,is a filter.
Further, the first threshold, the second threshold, the third threshold and the adaptive residual have the following relation:
wherein r is an adaptive residual error threshold value, C 1 、C 2 、C 3 A first threshold value, a second threshold value and a third threshold value respectively,is a filter.
The aeroengine execution loop fault detection method based on the adaptive comparator provided by the application has the following advantages:
1) Compared with the traditional fault detection method, the fault detection of soft faults can be realized by the model-based execution loop fault diagnosis method, and the method is also effective for smaller paranoid faults;
2) The fault detection method of the execution loop based on the model has short fault judgment time (usually 3 control periods) and lower false alarm rate and false alarm rate.
Drawings
In order to more clearly illustrate the technical solution provided by the present application, the following description will briefly refer to the accompanying drawings. It will be apparent that the figures described below are merely some embodiments of the application.
FIG. 1 is a schematic diagram of an execution loop model according to the present application.
Fig. 2 is a schematic diagram of adaptive threshold values in the present application.
FIG. 3 is a schematic diagram showing the comparison of model output and test data according to an embodiment of the present application.
FIG. 4 is a schematic diagram illustrating a balanced current drift fault according to an embodiment of the present application.
Fig. 5 is a schematic diagram of an oil leakage failure of an actuator according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application become more apparent, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the accompanying drawings in the embodiments of the present application.
The application provides an aeroengine execution loop fault detection method based on a self-adaptive comparator, in the method, firstly, an execution loop model for fault detection is established, and loop fault detection is carried out by utilizing the residual error of the output value and the real feedback value of the execution loop model, so that the output value of an execution mechanism is closer to the actual feedback value of the execution mechanism than the planned value of the execution mechanism in the transition state process, the selected fault judgment threshold value is greatly reduced, the fault judgment accuracy is improved, and the false alarm fault is reduced; secondly, an actuator model comprising nonlinear links such as actuator position, velocity saturation and the like is established, so that the application range of fault diagnosis based on the model is enlarged, and particularly, the scene of large-range transition state movement of an actuator loop is enlarged; finally, the method not only utilizes the deviation between the output value and the feedback value of the control variable model, but also designs the self-adaptive threshold value by utilizing the control quantity information, thereby effectively solving the problem of incompatibility of the steady state threshold value and the transition state threshold value and improving the real-time performance and the accuracy of fault detection of the execution loop.
In the application, the execution loop model comprises a main fuel metering execution loop model, a boost fuel metering execution loop model, an angle execution loop model, a nozzle area execution loop model and the like.
In the main fuel metering execution loop model, the main fuel metering mechanism comprises a main fuel servo valve, a follow-up piston and a main fuel metering valve, and the change of an electric signal can change the upper cavity pressure of the follow-up piston, so that the follow-up piston moves up and down, and the opening degree of the main fuel metering valve is controlled to provide required oil quantity. The state variable is the displacement of the main fuel metering valve, the control quantity selects the electric signal of the main fuel servo valve, and the speed and the position saturation limit are set in the model.
In the forced fuel metering execution loop model, the forced fuel metering mechanism comprises a forced fuel servo valve and a forced fuel metering valve, and the opening degree of the forced fuel metering valve is controlled by an electric signal so as to provide required oil quantity. The state variable is the displacement of the stressing fuel metering valve, the control quantity is the electric signal of the stressing fuel servo valve, and the model sets the speed and the position saturation limit.
In the angle execution loop model, an execution mechanism with an adjustable blade angle at a fan inlet, an adjustable stator blade angle at a high-pressure compressor inlet and a vector spray pipe angle consists of a servo valve and an actuator cylinder. The state variable is the displacement of the actuator cylinder, and the control quantity is the electric signal of the servo valve. The change of the electric signal of the servo valve changes the flow to the cavity of the actuator cylinder, so that pressure difference is generated at two ends of the actuator cylinder to move the actuator cylinder, and the angle of the adjustable angle position mechanism is driven to change.
In the spout area executing loop model, the spout area executing mechanism consists of a servo valve, an oil distributing valve and an actuating cylinder. The change of the electric signal of the servo valve causes the pressure of the upper cavity of the oil distributing valve to change, and further causes the sliding valve of the oil distributing valve to move; the displacement change of the oil distributing valve slide valve also changes the flow area of high-pressure oil and low-pressure oil to the cavity of the actuating cylinder, and pressure difference is generated at the two ends of the actuating cylinder to move the actuating cylinder, so that the size of the nozzle area is changed. The outlet area of the spray pipe comprises a double ring, the state variable is the displacement of the oil distributing valve and the displacement of the actuating cylinder, and the control quantity is the electric signal of the servo valve.
In the application, a residual error is generated by adopting the output value of the actuator loop model and the real sensor feedback value of the actuator loop, and if the residual error is larger than a given threshold value, the servo loop is determined to have a fault after the fault judging time is exceeded. And setting an adaptive residual error threshold by utilizing the relation between the control deviation and the control quantity amplitude and frequency, wherein the adaptive residual error threshold comprises a steady state error threshold, a static threshold proportional to the control quantity and a dynamic threshold related to the control quantity change. Wherein the transition state threshold is amplified using a first order high pass filter, and then the sum of the three thresholds is smoothed using a low pass filter.
The main fuel metering execution circuit is taken as an example for unfolding the explanation, and the rest of the aero-engine execution circuits are basically the same as the main fuel metering execution circuit in method and steps.
The method comprises the following specific processes:
1. establishing an execution loop model of a main fuel metering execution mechanism
As described above, the main fuel metering mechanism includes the slave piston and the main fuel metering valve, and the change of the current signal changes the pressure in the upper chamber of the slave piston, so as to move the slave piston up and down, and further control the opening of the metering valve to provide the required fuel amount, where the state variable is the displacement of the metering valve, and the control quantity is the current signal, so that there is:
1.1 Obtaining a deviation amount according to the displacement planning value LmDem of the execution loop and the displacement output value Lm_mdl of the fault detection model: e=lmdem-lm_mdl
1.2 The controller output current I and the balance current i_bal in the actuator have the following relationship:wherein k is p Is a proportional control coefficient, T i And T D Respectively an integral time constant and a differential time constant, wherein t is time;
1.3 The output current I of the controller is subtracted from the expected balance current I_BAL to obtain the input current delta I of the servo valve;
ΔI＝I-I_BAL
1.4 Because the natural frequency of the metering valve in the execution loop is far lower than the bandwidth of the servo valve, the transfer function model of the servo valve can be approximately represented by a second-order link, and the mathematical prototype of the valve in the execution loop is equivalent by an integrator. In addition, there is a small delay between the process of establishing the driving force and the process of establishing the flow, and the delay function is adopted for simulation. Equivalent second order transfer function through servo valveObtaining a flow difference DeltaQ of the electrohydraulic servo valve, performing Delay processing of a Delay link Delay_Lm on the flow to obtain a single-step integral quantity of the displacement of the metering valve, and obtaining the displacement of the metering valve after integration;
1.5 A limit response speed exists when the valve is operated, the limit speed is usually related to the saturated flow of the servo valve, the single-step integral quantity is limited to be not more than an upper limit and a lower limit, the limited single-step integral is accumulated, the range of the valve movement travel is limited, and finally the airborne fault detection model Lm_mdl is obtained:
where Kac is the loop gain, w is the natural frequency, and ζ is the damping ratio.
The fault detection model structures of the boost fuel oil executing circuit, the fan inlet adjustable blade angle executing circuit, the high-pressure compressor inlet adjustable stator blade angle executing circuit, the vector spray pipe angle executing circuit and the nozzle area executing circuit are consistent with the above.
2. Closed loop fault detection
At present, the digital electronic controller has a BIT (built-in-test) function, so that the fault detection of the digital electronic controller generally does not need to use a model, the current output is considered to be fault-free, and the loop fault detection is performed on the premise. Generating residual errors by adopting the output of the execution loop model and the feedback value of a real linear displacement sensor of the execution loop; and if the residual error is larger than the given threshold value, confirming the fault judging time, and then confirming the servo loop fault.
2.1 Determining a first threshold value for steady state fault diagnosis as C 1 First threshold C 1 Is a constant;
2.2 A) controlling the output current value I to obtain a filtered current value after filtering
2.3 Filtering electricThe value I_f can obtain a second threshold C by looking up a first reference table or curve 2 The control output current value I can be obtained through detection, the filtering current value I_f is obtained through constructing a relation between the control output current value I and the filtering current value I_f, and the first table or the curve can be obtained through fitting the filtering current value I_f;
2.4 Obtaining a third threshold C by controlling the output current value I to look up a second reference table/curve 3 Fitting the control output current value I to obtain the second reference table/curve;
2.5 The adaptive residual threshold r is based on the sum of three residual thresholds and is smoothed by a filter;
and comparing the absolute value of the difference value obtained according to the feedback value Lm (acquired by a sensor) of the execution loop and the model output value lm_mdl with the self-adaptive residual error r, and sending out a fault signal after the feedback value Lm is greater than or equal to 0 and the confirmation period is reached.
Taking a certain double-rotor small-bypass-ratio turbofan engine full authority control system as an example, an execution loop model of the engine is established by adopting the method, and an execution mechanism comprises an electrohydraulic servo valve and an actuating cylinder: the gain from the whole loop current to the position of the actuator cylinder is-12 mm/mA; the rate limiting range is-250-270 mm/mA/s; the displacement range is limited to-5-90 mm. By adopting the method, the open-loop model is compared and verified by using a certain typical test data, the real output current of the digital electronic controller is used as the input of the open-loop model, and the displacement change of the actual actuator cylinder is compared with the model output, as shown in figure 3, so that the model can be used as the model for the diagnosis of the airborne faults.
First threshold C 1 Set to 1.5mm, the second threshold C 2 Slope 0.015mm/mA in the graph, slope 0.3mm/mA in the graph of the third threshold C3, T 1 ＝0.8s，T 2 ＝0.4s，T 3 Control parameter kp= -0.8mA/mm, ki= -0.006mA/mm/s, kd=0.
As shown in the balance current drift fault simulation test in FIG. 4, when the balance current of the loop drifts by 5mA, the fault can be diagnosed after the residual exceeds the self-adaptive threshold value for 3 control periods, but the fault can not be diagnosed through the conventional extremum and slope fault, and the fault can not be diagnosed through the deviation of the planned value and the feedback value of the position of the loop after the steady state.
As shown in fig. 4, the fault can be diagnosed after the residual exceeds the adaptive threshold for 3 control cycles by the actuator leakage fault simulation test, but the fault cannot be diagnosed by the conventional extremum and slope fault, and the fault cannot be diagnosed by the deviation of the loop position planning value and the feedback value after the steady state.
The aeroengine execution loop fault detection method based on the adaptive comparator provided by the application has the following advantages:
1) Compared with the traditional fault detection method, the fault detection of soft faults can be realized by the model-based execution loop fault diagnosis method, and the method is also effective for smaller paranoid faults;
2) The fault detection method of the execution loop based on the model has short fault judgment time (usually 3 control periods) and lower false alarm rate and false alarm rate.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present application should be included in the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. An aeroengine execution loop fault detection method based on an adaptive comparator is characterized by comprising the following steps of:
determining an execution loop and an execution loop model in the aero-engine, and constructing a fault detection model according to the execution loop model;
determining a first threshold for fault detection in a steady state condition;
filtering according to the acquired control current value to obtain a filtered current value, fitting the filtered current value to obtain a first reference table of the relation between a second threshold value and the filtered current value, and inquiring the first reference table to obtain a second threshold value corresponding to the filtered current value under the control current value;
fitting the control current value to obtain a second reference table of the relation between a third threshold value and the control current value, and inquiring the second reference table to obtain a third threshold value corresponding to the control current value;
constructing a relation between a first threshold, a second threshold, a third threshold and the self-adaptive residual;
and comparing the relation between the absolute value of the difference between the feedback value of the execution loop and the output value of the fault detection model and the self-adaptive residual error threshold, and when the relation is greater than or equal to zero and reaches a plurality of periods, the execution loop fails, otherwise, the execution loop does not fail.
2. The adaptive comparator-based aircraft engine execution circuit fault detection method of claim 1, wherein the execution circuit in the aircraft engine comprises a main fuel metering execution circuit, a boost fuel metering execution circuit, an angle execution circuit, and a nozzle area execution circuit.
3. The method for detecting a fault in an execution loop of an aircraft engine based on an adaptive comparator according to claim 1 or 2, wherein the process of constructing the fault detection model from the execution loop model comprises:
according to the displacement plan value of the execution loop and the displacement output value of the fault detection model, a deviation amount e is obtained;
constructing a relation between the output current I of the controller and the balance current I_BAL in the actuating mechanism;
subtracting the expected balance current I_BAL from the controller output current I to obtain the input current of the servo valve;
adopting a second-order link to approximately represent a transfer function model of the servo valve, adopting a mathematical prototype to equivalently execute a valve in a loop by using an integrator, adopting a delay function to simulate a driving force process and a flow establishing process, obtaining a flow difference of the electrohydraulic servo valve after the equivalent second-order transfer function of the servo valve, performing delay processing of the delay link on the flow to obtain a single-step integral quantity of the displacement of the metering valve, and obtaining the displacement of the metering valve after integration;
and limiting the upper limit and the lower limit of the single-step integral quantity, accumulating the limited single-step integral, and limiting the range of the valve movement travel to finally obtain the airborne fault detection model.
4. A method for detecting a fault in an execution circuit of an aeroengine based on an adaptive comparator as claimed in claim 3, wherein the output current I of the controller and the balance current i_bal in the actuator have the following relationship:
wherein k is p Is a proportional control coefficient, e is a deviation amount, T i And T D The integral time constant and the differential time constant are respectively, and t is time.
5. The method for detecting the fault of the execution loop of the aeroengine based on the adaptive comparator as claimed in claim 4, wherein the input current Δi of the servo valve is:
ΔI＝I-I_BAL。
6. the method for detecting the fault of the execution loop of the aeroengine based on the adaptive comparator as claimed in claim 5, wherein the transfer function model of the second-order link is:
where Kac is the loop gain, w is the natural frequency, and ζ is the damping ratio.
7. The adaptive comparator-based aeroengine execution loop fault detection method of claim 6, wherein the fault detection model is:
in the formula, lm_mdl is a fault detection model, delay_lm is a Delay link, and Δi is a servo valve input current.
8. The adaptive comparator-based aeroengine execution loop fault detection method of claim 7, wherein the control output current value I and the filtered current value i_f satisfy the following:
in the method, in the process of the application,is a filter.
9. The adaptive comparator-based aircraft engine execution loop fault detection method of claim 8, wherein the first, second, third and adaptive residuals have the following relationship:
wherein r is an adaptive residual error threshold value, C 1 、C 2 、C 3 A first threshold value, a second threshold value and a third threshold value respectively,is a filter.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111432839.9A CN114237199B (en) | 2021-11-29 | 2021-11-29 | Aeroengine execution loop fault detection method based on adaptive comparator |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111432839.9A CN114237199B (en) | 2021-11-29 | 2021-11-29 | Aeroengine execution loop fault detection method based on adaptive comparator |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114237199A CN114237199A (en) | 2022-03-25 |
| CN114237199B true CN114237199B (en) | 2023-10-24 |
Family
ID=80751798
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111432839.9A Active CN114237199B (en) | 2021-11-29 | 2021-11-29 | Aeroengine execution loop fault detection method based on adaptive comparator |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114237199B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114265368B (en) * | 2021-12-07 | 2023-07-25 | 中国航发控制系统研究所 | Combined state self-adaptive estimation method for aero-engine servo control system |
| CN116107293B (en) * | 2023-04-10 | 2023-06-16 | 商飞软件有限公司 | Civil aircraft flight control system actuation loop fault diagnosis system and diagnosis method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2852077A1 (en) * | 2013-05-22 | 2014-11-22 | Air China Limited | Apparatus and method for testing aircraft message trigger logics |
| CN106682692A (en) * | 2016-12-22 | 2017-05-17 | 西北工业大学 | Method for structuring hydraulic steering loop fault diagnosis system based on SVR multiple models |
| CN107544459A (en) * | 2017-09-05 | 2018-01-05 | 北京控制工程研究所 | A kind of Multiple Failure Diagnosis optimization method of control system |
| CN107614216A (en) * | 2015-05-25 | 2018-01-19 | 日产自动车株式会社 | Trouble-shooter and method for diagnosing faults |
| CN110879584A (en) * | 2019-09-29 | 2020-03-13 | 北京动力机械研究所 | Turbofan engine comprehensive simulation test and fault injection platform for unmanned aerial vehicle |
| CN110879372A (en) * | 2019-12-03 | 2020-03-13 | 中南大学 | Traction system main loop earth fault diagnosis method and system based on feature correlation |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6856905B2 (en) * | 2003-04-29 | 2005-02-15 | Garmin At, Inc. | Systems and methods for fault detection and exclusion in navigational systems |
| US7062370B2 (en) * | 2004-03-30 | 2006-06-13 | Honeywell International Inc. | Model-based detection, diagnosis of turbine engine faults |
| US8555613B2 (en) * | 2009-03-02 | 2013-10-15 | GM Global Technology Operations LLC | Model-based diagnostics of NOx sensor malfunction for selective catalyst reduction system |
-
2021
- 2021-11-29 CN CN202111432839.9A patent/CN114237199B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2852077A1 (en) * | 2013-05-22 | 2014-11-22 | Air China Limited | Apparatus and method for testing aircraft message trigger logics |
| CN107614216A (en) * | 2015-05-25 | 2018-01-19 | 日产自动车株式会社 | Trouble-shooter and method for diagnosing faults |
| CN106682692A (en) * | 2016-12-22 | 2017-05-17 | 西北工业大学 | Method for structuring hydraulic steering loop fault diagnosis system based on SVR multiple models |
| CN107544459A (en) * | 2017-09-05 | 2018-01-05 | 北京控制工程研究所 | A kind of Multiple Failure Diagnosis optimization method of control system |
| CN110879584A (en) * | 2019-09-29 | 2020-03-13 | 北京动力机械研究所 | Turbofan engine comprehensive simulation test and fault injection platform for unmanned aerial vehicle |
| CN110879372A (en) * | 2019-12-03 | 2020-03-13 | 中南大学 | Traction system main loop earth fault diagnosis method and system based on feature correlation |
Non-Patent Citations (2)
| Title |
|---|
| Modeling and Fault Diagnosis of Aero-engine Lubricating Oil System;Qi Peng;《2018 37th Chinese Control Conference (CCC)》;全文 * |
| 航空发动机数控系统执行机构回路故障诊断和容错控制方法;蒋平国;《航空动力学报》;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114237199A (en) | 2022-03-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114237199B (en) | Aeroengine execution loop fault detection method based on adaptive comparator | |
| Zhang et al. | Robust adaptive fault-tolerant control for a class of unknown nonlinear systems | |
| US7970583B2 (en) | Degraded actuator detection | |
| CN104345638B (en) | A kind of active disturbance rejection self-adaptation control method of hydraulic motor positional servosystem | |
| US5233512A (en) | Method and apparatus for actuator fault detection | |
| Yao et al. | Nonlinear adaptive robust backstepping force control of hydraulic load simulator: Theory and experiments | |
| Borello et al. | A prognostic model for electrohydraulic servovalves | |
| Ding et al. | Sensor-fault-tolerant operation for the independent metering control system | |
| JP2013181536A (en) | Method and apparatus for local loop closure | |
| Ma et al. | Detection and adaptive accommodation for actuator faults of a class of non-linear systems | |
| Fadel et al. | Modeling, simulation and control of a fly-by-wire flight control system using classical PID and modified PI-D controllers | |
| Zhang et al. | SAR performance-based fault diagnosis for electro-hydraulic control system: A novel FDI framework for closed-loop system | |
| CN113515047B (en) | Fault detection method, device and equipment of displacement sensor | |
| CN108279569B (en) | State estimation method for hysteresis sandwich system with fault | |
| CN107942665B (en) | Modular active disturbance rejection control method for angular rate proportional-integral feedback | |
| Polas et al. | A multi-gain sliding mode based controller for the pitch angle control of a civil aircraft | |
| CN116220921A (en) | Method for generating dynamic characteristic evaluation index of executing mechanism of spout control loop | |
| CN114296346A (en) | Electro-hydraulic position servo system reconstruction control method and device based on fuzzy active disturbance rejection control | |
| US11552582B2 (en) | Setpoint identification on retrofit electric actuation | |
| Nagammai et al. | Design of optimal controllers for a three tank process | |
| Vanek et al. | Fault detection of electrical flight control system actuators using parameter dependent estimation | |
| Ma et al. | A novel RFDI-FTC system for thrust-vectoring aircraft undergoing control surface damage and actuator faults during supermaneuverable flight | |
| RU2710944C1 (en) | Method of control of hydraulic turbines (versions) | |
| Zhu et al. | Prescribed performance control for MDF continuous hot pressing hydraulic system | |
| Schmidt et al. | Second order sliding mode control with prescribed convergence law for electro-hydraulic drives |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |