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A Simulation Study Of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques
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Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781729368763 Total Pages :52 pages Book Rating :4.3/5 (687 download)
Book Synopsis A Simulation Study of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques by : National Aeronautics and Space Adm Nasa
Download or read book A Simulation Study of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-11 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deterioration of engine components may cause off-normal engine operation. The result is an unecessary loss of performance, because the fixed schedules are designed to accommodate a wide range of engine health. These fixed control schedules may not be optimal for a deteriorated engine. This problem may be solved by including a measure of deterioration in determining the control variables. These engine deterioration parameters usually cannot be measured directly but can be estimated. A Kalman filter design is presented for estimating two performance parameters that account for engine deterioration: high and low pressure turbine delta efficiencies. The delta efficiency parameters model variations of the high and low pressure turbine efficiencies from nominal values. The filter has a design condition of Mach 0.90, 30,000 ft altitude, and 47 deg power level angle (PLA). It was evaluated using a nonlinear simulation of the F100 engine model derivative (EMD) engine, at the design Mach number and altitude over a PLA range of 43 to 55 deg. It was found that known high pressure turbine delta efficiencies of -2.5 percent and low pressure turbine delta efficiencies of -1.0 percent can be estimated with an accuracy of + or - 0.25 percent efficiency with a Kalman filter. If both the high and low pressure turbine are deteriorated, the delta efficiencies of -2.5 percent to both turbines can be estimated with the same accuracy. Lambert, Heather H. Armstrong Flight Research Center RTOP 533-02-21...
Book Synopsis A Simulation Study of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques by :
Download or read book A Simulation Study of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques written by and published by . This book was released on 1991 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering by :
Download or read book Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering written by and published by . This book was released on 2003 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
Book Synopsis Kalman Filtering With Inequality Constraints for Turbofan Engine Health Estimation by :
Download or read book Kalman Filtering With Inequality Constraints for Turbofan Engine Health Estimation written by and published by . This book was released on 2003 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satis- fied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estima- tion accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model con- tains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781724120250 Total Pages :28 pages Book Rating :4.1/5 (22 download)
Book Synopsis Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering by : National Aeronautics and Space Adm Nasa
Download or read book Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-09-28 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering. Simon, Dan and Simon, Donald L. Glenn Research Center NASA/TM-2003-212528, ARL-TR-2956, GT2003-38584, E-14090, NAS 1.15:212528...
Author :National Aeronautics and Space Administration (NASA) Publisher :Createspace Independent Publishing Platform ISBN 13 :9781721590476 Total Pages :28 pages Book Rating :4.5/5 (94 download)
Book Synopsis Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering by : National Aeronautics and Space Administration (NASA)
Download or read book Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-06-20 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering. Simon, Dan and Simon, Donald L. Glenn Research Center NASA/TM-2003-212528, ARL-TR-2956, GT2003-38584, E-14090, NAS 1.15:212528
Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781723734168 Total Pages :38 pages Book Rating :4.7/5 (341 download)
Book Synopsis Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation by : National Aeronautics and Space Adm Nasa
Download or read book Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-09-15 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satisfied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.Simon, Dan and Simon, Donald L.Glenn Research CenterTURBOFAN ENGINES; AIRCRAFT ENGINES; KALMAN FILTERS; QUADRATIC PROGRAMMING; SYSTEMS HEALTH MONITORING; GAS TURBINE ENGINES; ALGORITHMS; ESTIMATES; INEQUALITIES; SIMULATION
Author :National Aeronautics and Space Administration (NASA) Publisher :Createspace Independent Publishing Platform ISBN 13 :9781720451761 Total Pages :28 pages Book Rating :4.4/5 (517 download)
Book Synopsis Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation by : National Aeronautics and Space Administration (NASA)
Download or read book Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-05-29 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).Simon, Dan and Simon, Donald L.Glenn Research CenterTURBOFAN ENGINES; PROBABILITY THEORY; KALMAN FILTERS; AIRCRAFT ENGINES; FLIGHT SAFETY; INEQUALITIES; SIMULATION
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation by : National Aeronaut Administration (Nasa)
Download or read book Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation written by National Aeronaut Administration (Nasa) and published by . This book was released on 2020-08-05 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health. Simon, Dan and Simon, Donald L. Glenn Research Center NASA/TM-2005-213962, ARL-MR-621, E-15278 TURBOFAN ENGINES; KALMAN FILTERS; ESTIMATES; HEURISTIC METHODS; RISK; SIMULATION; INEQUALITIES
Book Synopsis Application of a Bank of Kalman Filters for Aircraft Engine Fault Diagnostics by :
Download or read book Application of a Bank of Kalman Filters for Aircraft Engine Fault Diagnostics written by and published by . This book was released on 2003 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, a bank of Kalman filters is applied to aircraft gas turbine engine sensor and actuator fault detection and isolation (FDI) in conjunction with the detection of component faults. This approach uses multiple Kalman filters, each of which is designed for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, thereby isolating the specific fault. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The proposed FDI approach is applied to a nonlinear engine simulation at nominal and aged conditions, and the evaluation results for various engine faults at cruise operating conditions are given. The ability of the proposed approach to reliably detect and isolate sensor and actuator faults is demonstrated. (7 tables, 4 figures, 17 refs.).
Book Synopsis Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation by : Nasa Technical Reports Server (Ntrs)
Download or read book Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation written by Nasa Technical Reports Server (Ntrs) and published by BiblioGov. This book was released on 2013-07 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters.
Book Synopsis A Proposed Kalman Filter Algorithm for Estimation of Unmeasured Output Variables for an F100 Turbofan Engine by : Gurbux S. Alag
Download or read book A Proposed Kalman Filter Algorithm for Estimation of Unmeasured Output Variables for an F100 Turbofan Engine written by Gurbux S. Alag and published by . This book was released on 1990 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filter Estimation of Engine Deterioration by : Heather H. Lambert
Download or read book Kalman Filter Estimation of Engine Deterioration written by Heather H. Lambert and published by . This book was released on 1989 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :National Aeronautics and Space Administration (NASA) Publisher :Createspace Independent Publishing Platform ISBN 13 :9781721804122 Total Pages :34 pages Book Rating :4.8/5 (41 download)
Book Synopsis Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters by : National Aeronautics and Space Administration (NASA)
Download or read book Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-06-24 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: An approach based on the Constant Gain Extended Kalman Filter (CGEKF) technique is investigated for the in-flight estimation of non-measurable performance parameters of aircraft engines. Performance parameters, such as thrust and stall margins, provide crucial information for operating an aircraft engine in a safe and efficient manner, but they cannot be directly measured during flight. A technique to accurately estimate these parameters is, therefore, essential for further enhancement of engine operation. In this paper, a CGEKF is developed by combining an on-board engine model and a single Kalman gain matrix. In order to make the on-board engine model adaptive to the real engine s performance variations due to degradation or anomalies, the CGEKF is designed with the ability to adjust its performance through the adjustment of artificial parameters called tuning parameters. With this design approach, the CGEKF can maintain accurate estimation performance when it is applied to aircraft engines at offnominal conditions. The performance of the CGEKF is evaluated in a simulation environment using numerous component degradation and fault scenarios at multiple operating conditions. Kobayashi, Takahisa and Simon, Donald L. and Litt, Jonathan S. Glenn Research Center NASA/TM-2005-213865, E-15235, ARL-TR-3489, GT2005-68494
Download or read book NASA SP. written by and published by . This book was released on 1992 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation by : Nasa Technical Reports Server (Ntrs)
Download or read book Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation written by Nasa Technical Reports Server (Ntrs) and published by BiblioGov. This book was released on 2013-07 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.
