CN110083076A - A kind of gas turbine pneumatic actuator failure semi-physical emulation platform and emulation mode - Google Patents
A kind of gas turbine pneumatic actuator failure semi-physical emulation platform and emulation mode Download PDFInfo
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Abstract
The invention discloses a kind of gas turbine pneumatic actuator failure semi-physical emulation platforms and emulation mode that belong to gas-turbine installation field, comprising: dSPACE control module, MATLAB/Simulink emulation module and in-kind portion；MATLAB/Simulink emulation module includes Collection submodule, fault diagnosis submodule and control instruction submodule, it and also include trouble-free gas turbine pneumatic actuator model, the state vector generated by it can be compared with collected pneumatic actuator malfunction vector, generate the residual error for having fault message.The present invention is by designing a kind of gas turbine pneumatic actuator failure semi-physical emulation platform and emulation mode, to reduce the miscalculation rate for examining method for diagnosing faults, the safety for improving inspection method for diagnosing faults, the fault diagnosis technology of pneumatic actuator fault message can promptly and accurately be obtained by being conducive to exploitation.
Description
Technical field
The invention belongs to gas-turbine installation technical field, specially a kind of gas turbine pneumatic actuator failure half is in kind
Emulation platform and emulation mode.
Background technique
With the development of the global economy with social progress, the problems such as energy crisis, environmental pollution becomes increasingly conspicuous, and cleans energy
Research, the development and utilization in source have obtained swift and violent development.Natural gas as a kind of clean energy resource, have alleviate energy shortage,
Coal fired power generation ratio is reduced, the advantages that reducing environmental pollution.Although gas turbine has high efficiency, low noise, low emission etc. one
Serial advanced technology feature, but its structure is complicated, works under high temperature, high pressure and high-revolving harsh environments, is easy to
Various failures occur.According to statistics, failure of the 80% gas turbine control system failure due to sensor and actuator.
Pneumatic actuator has many advantages, such as that simple structure, reliable in action, steady, thrust output is big, in gas turbine unit
The middle more other kinds of executing agency of application is more extensive.Therefore, the research of gas turbine pneumatic actuator fault diagnosis has
Highly important meaning.
At present in the research process of gas turbine pneumatic actuator fault diagnosis, object test is essential key
Step.But since by calculating that the factors such as data error are limited, the field adjustable of gas turbine control system becomes extremely to be stranded
It is difficult.Therefore, carrying out the HWIL simulation of pneumatic actuator failure in laboratory conditions is that gas turbine pneumatic actuator failure is examined
The important means of disconnected research.
It, can be with we have proposed a kind of gas turbine pneumatic actuator failure semi-physical emulation platform for this problem
It quickly and easily modifies, replace fault diagnosis algorithm, and overcome gas turbine pneumatic actuator fault diagnosis research scene and survey
Try difficult defect.
Summary of the invention
The problem of for background technique, the present invention provides a kind of gas turbine pneumatic actuator failure half is in kind
Emulation platform, which is characterized in that it is characterised by comprising: dSPACE control module and being connected respectively with dSPACE control module
MATLAB/Simulink emulation module and in-kind portion；Wherein MATLAB/Simulink emulation module includes what sequence was connected
Collection submodule, fault diagnosis submodule and control instruction submodule；Wherein Collection submodule is used for
Position, the temperature, pressure signal for acquiring pneumatic actuator, obtain the malfunction vector x (t) of pneumatic actuator；Fault diagnosis
The signal of acquisition is carried out time-domain analysis and frequency-domain analysis by submodule, by being compared with fault-free pneumatic actuator state vector
Compared with generation has the residual epsilon (t) of fault message, is handled using fault diagnosis algorithm residual error to obtain pneumatic actuator event
Hinder type f and failure strength Sf；Control instruction submodule issues control to failure pneumatic actuator according to fault diagnosis result and refers to
Enable u (t)；
DSPACE control module includes connected A/D submodule, bus submodule and the D/A submodule of sequence；
In-kind portion includes pneumatic actuator module interconnected and supplementary module, and wherein pneumatic actuator module passes through
The method of direct fault location realizes the simulation of a variety of typical faults of pneumatic actuator, and by analog result send to vibrating sensor,
Pneumatic adjusting mechanism for adjusting, solenoid valve and valve positioner；Supplementary module is for maintaining failure pneumatic actuator to be safely operated.
Include trouble-free gas turbine pneumatic actuator model in the MATLAB/Simulink emulation module, passes through
Its state vector x generatedn(t) it can be compared with collected pneumatic actuator malfunction vector x (t), generate band
The residual epsilon (t) of faulty information, the specific steps are as follows:
Step 2.1: control instruction submodule is pneumatically executed to pneumatic actuator module and trouble-free gas turbine respectively
Device model sends identical control instruction u (t)；
Step 2.2: after trouble-free gas turbine pneumatic actuator model receives control instruction u (t), can generate without reason
The state vector x of barriern(t):
Wherein, xnIt (t) is pneumatic actuator unfaulty conditions vector, P1nIt (t) is upstream pressure under normal condition, Pa；
P2nIt (t) is downstream pressure under normal condition, Pa；Xn(t) it is stem position under normal condition；FnIt (t) is under normal condition
Valve flow, m3/h；T1nIt (t) is fluid temperature (F.T.) in valve under normal condition, DEG C；en(t) it is valve rod position under normal condition
Set deviation；
Step 2.3: Collection submodule will acquire the real-time status of pneumatic actuator module, generate malfunction
Vector x (t):
Wherein, x (t) is pneumatic actuator malfunction vector, and P1 (t) is that upstream pressure sensor measures pressure, Pa；P2
It (t) is that downstream pressure sensor measures pressure, Pa；X (t) is that valve positioner measures stem position；F (t) is flowmeter after valve
Measure flow, m3/h；T1 (t) is that temperature sensor measures temperature in valve, DEG C；E (t) is practical valve rod position deviation value；
Step 2.4: malfunction vector x (t) and trouble-free state vector xn(t) comparison generates residual epsilon (t):
Wherein, xn(0) be initial time unfaulty conditions vector, xnIt (t) is pneumatic actuator unfaulty conditions vector, x
(0) be initial time malfunction vector, x (t) is malfunction vector, and σ is positive scalar constant value, and t is the fault simulation time,
s；t0For the initial time of fault simulation, s；τ is process intermediate variable, and n is the unit vector for residual error in state space.
The method of the direct fault location includes: hardware based direct fault location, software-based direct fault location and mixing event
Barrier injection；Fault type, time of failure and failure strength etc. can be set in the failure of injection, generates with fault message
Fault simulation signal Fs(t):
Wherein, fiFor fault type vector, tfsFor failure initial time, tesFor failure end time, texFor failure strength
Transformation period, MfsFor maximum failure strength, Mf0For failure original state.
According to fault simulation signal Fs(t) pneumatic actuator failure valve rod position signal X can be simulatedf(t) it and pneumatically holds
Row device failure valve flow Ff(t):
Xf(t)=(1-Fs(t))X(t) (5)
Ff(t)=Fs(t)F(t) (6)
Wherein, X (t) is that valve positioner measures stem position, and F (t) is that flow measurement obtains flow, m after valve3/h。
The supplementary module includes pipeline and sensor, pneumatic actuator gas source and bypass valve before and after pneumatic actuator；It is auxiliary
It helps module by the setting to multiple state thresholds, guarantees the safety of fault simulation process.
Fault diagnosis submodule is used to verify in the MATLAB/Simulink emulation module and more different failures is examined
Disconnected algorithm, verification step are as follows:
Step 5.1: by the pneumatic actuator module, selecting a kind of pneumatic actuator fault type, adjustment failure is strong
Degree and time of failure simulate the typical fault of gas turbine pneumatic actuator；
Step 5.2: the fault diagnosis algorithm verified needed for being added in the fault diagnosis submodule；
Step 5.3: may determine that by comparing fault diagnosis result and fault type initially set and failure strength
The accuracy of the fault diagnosis algorithm of required verifying:
Wherein, Q is observation space, Q0And Q1It is observation subspace, P (E0) it is pneumatic actuator probability of nonfailure, P (E1)
It is that pneumatic actuator breaks down probability, and P (q | E0) it is conditional probability of the pneumatic actuator fault-free under observation space, P (q |
E1) it is the conditional probability that pneumatic actuator breaks down under observation space, DfsIt is extrapolated for fault diagnosis algorithm to be verified
Maximum failure strength, MfsFor the maximum failure strength of setting；
The accuracy includes cailure rate of false positives Pw, failure rate of failing to report Po, fault detection error PeAnd failure strength detection misses
Poor Pfe。
Control instruction submodule is for verifying and more different fault-tolerant controls in the MATLAB/Simulink emulation module
Algorithm processed, verification step are as follows:
Step 6.1: by the pneumatic actuator module, selecting a kind of pneumatic actuator fault type, adjustment failure is strong
Degree and time of failure simulate the typical fault of gas turbine pneumatic actuator, are added and have been subjected in fault diagnosis module
Verify standard compliant fault diagnosis algorithm；
Step 6.2: the fault-tolerant control algorithm verified needed for being added in the control instruction generation module；
Step 6.3: by comparing under conditions of pneumatic actuator breaks down, stem position X (t) and valve flow F
(t), judge the feasibility of fault-tolerant control algorithm to be verified.
The beneficial effects of the present invention are:
1. being based on MATLAB/SIMULINK simulated environment, dSPACE control system, it can quickly and easily modify, replace
Fault diagnosis algorithm.
2. the present invention based on in-kind portion, is capable of the output characteristics of accurate simulation failure pneumatic actuator, operation ring
Border etc..Therefore the defect of gas turbine pneumatic actuator fault diagnosis research on-the-spot test difficulty is overcome.
3. the calculating and emulation to running pneumatic actuator static properties may be implemented in the present invention, inspection event is reduced
Hinder the miscalculation rate of diagnostic method, improve the safety for examining method for diagnosing faults, gas can promptly and accurately be obtained by being conducive to exploitation
The fault diagnosis technology of dynamic actuator failures information, in gas turbine control system fault diagnosis field practical valence with higher
Value.
Detailed description of the invention
Fig. 1 is a kind of structural block diagram of gas turbine pneumatic actuator failure semi-physical emulation platform embodiment of the present invention；
Fig. 2 is the connection figure of in-kind portion in the embodiment of the present invention；
Fig. 3 is pair of gas turbine pneumatic actuator model and practical pneumatic actuator stem position in the embodiment of the present invention
Than figure；
Fig. 4 is gas turbine pneumatic actuator model and practical pneumatic actuator inner valve flow in the embodiment of the present invention
Comparison diagram.
Specific embodiment
Below in conjunction with attached drawing, the present invention is described in further detail.
The embodiment of the present invention as shown in Figure 1, specifically includes: dSPACE control module and respectively with dSPACE control module
Connected MATLAB/Simulink emulation module and in-kind portion；Wherein MATLAB/Simulink emulation module includes sequence phase
Collection submodule, fault diagnosis submodule and control instruction submodule even；Wherein Collection submodule
The signals such as position, temperature, pressure for acquiring pneumatic actuator obtain the malfunction vector x (t) of pneumatic actuator；Therefore
The signal of acquisition is carried out time-domain analysis and frequency-domain analysis by barrier diagnosis submodule, by with fault-free pneumatic actuator state vector
It is compared, generates the residual epsilon (t) for having fault message, residual error is handled using fault diagnosis algorithm and is pneumatically held
Row device fault type f and failure strength Sf；Control instruction submodule issues failure pneumatic actuator according to fault diagnosis result
Control instruction u (t)；
DSPACE control module includes connected A/D submodule, bus submodule and the D/A submodule of sequence；Bus submodule
Block is used to transmit the information between MATLAB/Simulink emulation module and dSPACE control module, A/D submodule and D/A submodule
Block is used to transmit the information in in-kind portion between pneumatic actuator module and dSPACE control module.
In-kind portion as shown in Figure 2 includes pneumatic actuator module interconnected and supplementary module, wherein pneumatically holding
Row device module realizes the simulation of a variety of typical faults of pneumatic actuator by the method for direct fault location, and analog result is sent to
Vibrating sensor, Pneumatic adjusting mechanism for adjusting, solenoid valve and valve positioner；Supplementary module is for maintaining failure pneumatic actuator safe
Operation；Supplementary module includes pipeline and sensor (temperature sensor, flowmeter, pressure sensor), gas before and after pneumatic actuator
Dynamic actuator gas source (air compressor and its driver, air filtration pressure reducing valve), bypass valve etc..By to multiple state thresholds
Setting, supplementary module can guarantee the safety of fault simulation process.
Include trouble-free gas turbine pneumatic actuator model in MATLAB/Simulink emulation module, is given birth to by it
At state vector xn(t) can be compared with collected pneumatic actuator malfunction vector x (t), generate with therefore
Hinder the residual epsilon (t) of information, the specific steps are as follows:
Step 2.1: control instruction submodule is pneumatically executed to pneumatic actuator module and trouble-free gas turbine respectively
Device model sends identical control instruction u (t)；
Step 2.2: after trouble-free gas turbine pneumatic actuator model receives control instruction u (t), can generate without reason
The state vector x of barriern(t):
Wherein, xnIt (t) is pneumatic actuator unfaulty conditions vector, P1nIt (t) is upstream pressure under normal condition, Pa；
P2nIt (t) is downstream pressure under normal condition, Pa；Xn(t) it is stem position under normal condition；FnIt (t) is under normal condition
Valve flow, m3/h；T1nIt (t) is fluid temperature (F.T.) in valve under normal condition, DEG C；en(t) it is valve rod position under normal condition
Set deviation；
Step 2.3: Collection submodule will acquire the real-time status of pneumatic actuator module, generate malfunction
Vector x (t):
Wherein, x (t) is pneumatic actuator malfunction vector, and P1 (t) is that upstream pressure sensor measures pressure, Pa；P2
It (t) is that downstream pressure sensor measures pressure, Pa；X (t) is that valve positioner measures stem position；F (t) is flowmeter after valve
Measure flow, m3/h；T1 (t) is that temperature sensor measures temperature in valve, DEG C；E (t) is practical valve rod position deviation value；
Step 2.4: malfunction vector x (t) and trouble-free state vector xn(t) comparison generates residual epsilon (t):
Wherein, xn(0) be initial time unfaulty conditions vector, xnIt (t) is pneumatic actuator unfaulty conditions vector, x
(0) be initial time malfunction vector, x (t) is malfunction vector, and σ is positive scalar constant value, and t is the fault simulation time,
s；t0For the initial time of fault simulation, s；τ is process intermediate variable, and n is the unit vector for residual error in state space.
The method of direct fault location includes: hardware based direct fault location, software-based direct fault location and mixed fault note
Enter；Fault type, time of failure and failure strength etc. can be set in the failure of injection, generates the failure for having fault message
Analog signal Fs(t):
Wherein, fiFor fault type vector, tfsFor failure initial time, tesFor failure end time, texFor failure strength
Transformation period, MfsFor maximum failure strength, Mf0For failure original state.
According to fault simulation signal Fs(t) pneumatic actuator failure valve rod position signal X can be simulatedf(t) it and pneumatically holds
Row device failure valve flow Ff(t):
Xf(t)=(1-Fs(t))X(t) (5)
Ff(t)=Fs(f)F(t) (6)
Wherein, X (t) is that valve positioner measures stem position, and F (t) is that flow measurement obtains flow, m after valve3/h。
Fault diagnosis submodule is used to verify in MATLAB/Simulink emulation module and more different fault diagnosises is calculated
Method, verification step are as follows:
Step 5.1: by the pneumatic actuator module, selecting a kind of pneumatic actuator fault type, adjustment failure is strong
Degree and time of failure simulate the typical fault of gas turbine pneumatic actuator；
Step 5.2: the fault diagnosis algorithm verified needed for being added in the fault diagnosis submodule；
Step 5.3: may determine that by comparing fault diagnosis result and fault type initially set and failure strength
The accuracy of the fault diagnosis algorithm of required verifying (includes cailure rate of false positives Pw, failure rate of failing to report Po, fault detection error PeAnd
Failure strength detection error Pfe):
Wherein, Q is observation space, Q0And Q1It is observation subspace, P (E0) it is pneumatic actuator probability of nonfailure, P (E1)
It is that pneumatic actuator breaks down probability, and P (q | E0) it is conditional probability of the pneumatic actuator fault-free under observation space, P (q |
E1) it is the conditional probability that pneumatic actuator breaks down under observation space, DfsIt is extrapolated for fault diagnosis algorithm to be verified
Maximum failure strength, MfsFor the maximum failure strength of setting.
Control instruction submodule is used to verify in MATLAB/Simulink emulation module and more different faults-tolerant controls is calculated
Method, verification step are as follows:
Step 6.1: by the pneumatic actuator module, selecting a kind of pneumatic actuator fault type, adjustment failure is strong
Degree and time of failure simulate the typical fault of gas turbine pneumatic actuator, are added and have been subjected in fault diagnosis module
Verify standard compliant fault diagnosis algorithm；
Step 6.2: the fault-tolerant control algorithm verified needed for being added in the control instruction generation module；
Step 6.3: by comparing under conditions of pneumatic actuator breaks down, stem position X (t) and valve flow F
(t) (one kind is that controller output is corrected by fault-tolerant control algorithm to be verified；Another kind of is to repair without fault-tolerant control algorithm
Just), it can be determined that go out the feasibility of fault-tolerant control algorithm to be verified.
Gas turbine pneumatic actuator model and valve rod position of the practical pneumatic actuator within a hour as shown in Figure 3
Set X (t) comparing result.As can be seen that using pneumatic actuator model provided by the invention and practical pneumatic actuator in valve rod
The variation tendency of position is quite similar, and pneumatic actuator model and practical pneumatic actuator have very high similarity.
Gas turbine pneumatic actuator model and valve stream of the practical pneumatic actuator within a hour as shown in Figure 4
Measure F (t) comparing result.As can be seen that using pneumatic actuator model provided by the invention and practical pneumatic actuator in valve
The variation tendency similarity of flow is higher, and pneumatic actuator model accuracy is higher.
The present invention devises a kind of full on the basis of traditional gas turbine pneumatic actuator fault diagnosis object test
New gas turbine pneumatic actuator failure semi-physical emulation platform；It is controlled based on MATLAB/SIMULINK simulated environment, dSPACE
System processed can be modified quickly and easily, replace fault diagnosis algorithm；Moreover, analogue system is based on in-kind portion, it can
Output characteristics, the running environment etc. of accurate simulation failure pneumatic actuator.Therefore, the system overcomes gas turbine and pneumatically holds
The defect of row device fault diagnosis research on-the-spot test difficulty；Meanwhile emulation platform may be implemented to running pneumatic actuator
The calculating and emulation of static properties.Therefore, the system is in gas turbine control system fault diagnosis field reality with higher
With value.
Claims (6)
1. a kind of gas turbine pneumatic actuator failure semi-physical emulation platform, which is characterized in that the emulation platform by
DSPACE control module is connected to form with MATLAB/Simulink emulation module and in-kind portion respectively；Wherein MATLAB/
Simulink emulation module includes connected Collection submodule, fault diagnosis submodule and the control instruction submodule of sequence
Block；Wherein Collection submodule is used to acquire position, the temperature, pressure signal of pneumatic actuator, is pneumatically executed
The malfunction vector x (t) of device；The signal of acquisition is carried out time-domain analysis and frequency-domain analysis by fault diagnosis submodule, by with
Fault-free pneumatic actuator state vector is compared, and is generated the residual epsilon (t) for having fault message, is used fault diagnosis algorithm
Residual error is handled to obtain pneumatic actuator fault type f and failure strength Sf；Control instruction submodule is according to fault diagnosis
As a result control instruction u (t) is issued to failure pneumatic actuator；
DSPACE control module includes connected A/D submodule, bus submodule and the D/A submodule of sequence；
In-kind portion includes pneumatic actuator module interconnected and supplementary module, and wherein pneumatic actuator module passes through failure
The method of injection realizes the simulation of a variety of typical faults of pneumatic actuator, and sends analog result to vibrating sensor, pneumatic
Regulating mechanism, solenoid valve and valve positioner；Supplementary module is for maintaining failure pneumatic actuator to be safely operated.
2. gas turbine pneumatic actuator failure semi-physical emulation platform according to claim 1, which is characterized in that described
Supplementary module includes pipeline and sensor, pneumatic actuator gas source and bypass valve before and after pneumatic actuator；Supplementary module by pair
The setting of multiple state thresholds guarantees the safety of fault simulation process.
3. a kind of emulation mode of gas turbine pneumatic actuator failure semi-physical emulation platform as described in claim 1,
It is characterized in that, includes trouble-free gas turbine pneumatic actuator model in the MATLAB/Simulink emulation module, pass through
Its state vector x generatedn(t) it is compared with collected pneumatic actuator malfunction vector x (t), generation has
The residual epsilon (t) of fault message, the specific steps are as follows:
Step 2.1: control instruction submodule is respectively to pneumatic actuator module and trouble-free gas turbine pneumatic actuator mould
Type sends identical control instruction u (t)；
Step 2.2: after trouble-free gas turbine pneumatic actuator model receives control instruction u (t), can generate trouble-free
State vector xn(t):
Wherein, xnIt (t) is pneumatic actuator unfaulty conditions vector, P1nIt (t) is upstream pressure under normal condition, Pa；P2n
It (t) is downstream pressure under normal condition, Pa；Xn(t) it is stem position under normal condition；Fn(t) it is valve under normal condition
Door flow, m3/h；T1nIt (t) is fluid temperature (F.T.) in valve under normal condition, DEG C；enIt (t) is that stem position under normal condition is inclined
Difference；
Step 2.3: Collection submodule will acquire the real-time status of pneumatic actuator module, generate malfunction vector
X (t):
Wherein, x (t) is pneumatic actuator malfunction vector, and P1 (t) is that upstream pressure sensor measures pressure, Pa；P2(t)
It is that downstream pressure sensor measures pressure, Pa；X (t) is that valve positioner measures stem position；F (t) is that flow measurement obtains after valve
Flow, m3/h；T1 (t) is that temperature sensor measures temperature in valve, DEG C；E (t) is practical valve rod position deviation value；
Step 2.4: malfunction vector x (t) and trouble-free state vector xn(t) comparison generates residual epsilon (t):
Wherein, xn(0) be initial time unfaulty conditions vector, xnIt (t) is pneumatic actuator unfaulty conditions vector, x (0)
It is the malfunction vector of initial time, x (t) is malfunction vector, and σ is positive scalar constant value, and t is fault simulation time, s；
t0For the initial time of fault simulation, s；τ is process intermediate variable, and n is the unit vector for residual error in state space.
4. the emulation mode of gas turbine pneumatic actuator failure semi-physical emulation platform according to claim 3, special
Sign is that the method for the direct fault location includes: hardware based direct fault location, software-based direct fault location and mixed fault
Injection；Fault setting fault type, time of failure and the failure strength of injection generate the fault simulation for having fault message
Signal Fs(t):
Wherein, fiFor fault type vector, tfsFor failure initial time, tesFor failure end time, texFor failure strength variation
Time, MfsFor maximum failure strength, Mf0For failure original state；
According to fault simulation signal Fs(t) pneumatic actuator failure valve rod position signal X is simulatedf(t) and pneumatic actuator failures
Valve flow signal Ff(t):
Xf(t)=(1-Fs(t))X(t) (5)
Ff(t)=Fs(t)F(t) (6)
Wherein, X (t) is that valve positioner measures stem position, and F (t) is that flow measurement obtains flow, m after valve3/h。
5. the emulation mode of gas turbine pneumatic actuator failure semi-physical emulation platform according to claim 3, special
Sign is that fault diagnosis submodule is used to verify in the MATLAB/Simulink emulation module and more different failures is examined
Disconnected algorithm, verification step are as follows:
Step 5.1: by the pneumatic actuator module, select a kind of pneumatic actuator fault type, adjustment failure strength and
Time of failure simulates the typical fault of gas turbine pneumatic actuator；
Step 5.2: the fault diagnosis algorithm verified needed for being added in the fault diagnosis submodule；
Step 5.3: judging required verifying by comparing fault diagnosis result and fault type initially set and failure strength
Fault diagnosis algorithm accuracy:
Wherein, Q is observation space, Q0And Q1It is observation subspace, P (E0) it is pneumatic actuator probability of nonfailure, P (E1) it is pneumatic
Actuator breaks down probability, and P (q | E0) it is conditional probability of the pneumatic actuator fault-free under observation space, and P (q | E1) it is gas
The conditional probability that dynamic actuator breaks down under observation space, DfsThe most die extrapolated for fault diagnosis algorithm to be verified
Hinder intensity, MfsFor the maximum failure strength of setting；
The accuracy includes cailure rate of false positives Pw, failure rate of failing to report Po, fault detection error PeAnd failure strength detection error
Pfe。
6. the emulation mode of gas turbine pneumatic actuator failure semi-physical emulation platform according to claim 3, special
Sign is, control instruction submodule is for verifying and more different fault-tolerant controls in the MATLAB/Simulink emulation module
Algorithm processed, verification step are as follows:
Step 6.1: by the pneumatic actuator module, select a kind of pneumatic actuator fault type, adjustment failure strength and
Time of failure simulates the typical fault of gas turbine pneumatic actuator, is added in fault diagnosis module and has been subjected to verifying
Standard compliant fault diagnosis algorithm；
Step 6.2: the fault-tolerant control algorithm verified needed for being added in the control instruction generation module；
Step 6.3: by comparing under conditions of pneumatic actuator breaks down, stem position X (t) and valve flow F (t),
Judge the feasibility of fault-tolerant control algorithm to be verified.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110687901A (en) * | 2019-10-31 | 2020-01-14 | 重庆长安汽车股份有限公司 | Simulation test platform |
| CN110824955A (en) * | 2019-11-21 | 2020-02-21 | 上海电气燃气轮机有限公司 | dSPACE-based gas turbine combined simulation platform and method |
| CN111830943A (en) * | 2020-07-27 | 2020-10-27 | 华北电力大学 | Method for identifying faults of electric actuator of gas turbine |
| CN111857098A (en) * | 2020-07-27 | 2020-10-30 | 华北电力大学 | Fault diagnosis method of gas turbine electric actuator based on information statistical analysis |
| CN113011039A (en) * | 2021-03-31 | 2021-06-22 | 上海发电设备成套设计研究院有限责任公司 | Heavy gas turbine control system verification platform and verification method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201166793Y (en) * | 2007-09-13 | 2008-12-17 | 北京航空航天大学 | Controller for nobody machine earth surface emulation system base on singlechip |
-
2019
- 2019-05-30 CN CN201910462987.1A patent/CN110083076B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201166793Y (en) * | 2007-09-13 | 2008-12-17 | 北京航空航天大学 | Controller for nobody machine earth surface emulation system base on singlechip |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110687901A (en) * | 2019-10-31 | 2020-01-14 | 重庆长安汽车股份有限公司 | Simulation test platform |
| CN110824955A (en) * | 2019-11-21 | 2020-02-21 | 上海电气燃气轮机有限公司 | dSPACE-based gas turbine combined simulation platform and method |
| CN111830943A (en) * | 2020-07-27 | 2020-10-27 | 华北电力大学 | Method for identifying faults of electric actuator of gas turbine |
| CN111857098A (en) * | 2020-07-27 | 2020-10-30 | 华北电力大学 | Fault diagnosis method of gas turbine electric actuator based on information statistical analysis |
| CN111830943B (en) * | 2020-07-27 | 2022-07-29 | 华北电力大学 | Method for identifying faults of electric actuator of gas turbine |
| CN111857098B (en) * | 2020-07-27 | 2023-10-10 | 华北电力大学 | Fault diagnosis method for electric actuator of gas turbine based on information statistical analysis |
| CN113011039A (en) * | 2021-03-31 | 2021-06-22 | 上海发电设备成套设计研究院有限责任公司 | Heavy gas turbine control system verification platform and verification method |
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