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Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

Lu F, Huang J, Xing Y - Sensors (Basel) (2012)

Bottom Line: The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight.Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated.When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference.

View Article: PubMed Central - PubMed

Affiliation: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. lfaann@nuaa.edu.cn

ABSTRACT
Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

No MeSH data available.


Related in: MedlinePlus

The response to step input by (a) PI controller with no delay; and (b) PID controller with delay.
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f6-sensors-12-11061: The response to step input by (a) PI controller with no delay; and (b) PID controller with delay.

Mentions: The control system should maintain the parameter ng to the reference under the gas turbine mode, for which proportional plus integral (PI) controller is used. When proportional gain Kp = 200 and integral gain KI = 600, the step response for a 1% step input under the steady state of ng% = 85% is shown in Figure 6(a). In order to discriminate and eliminate outliers, the sensed data ng is held for two time steps to determine the variances in Equations (14–16). If we still select PI controller, the control system will become unsteady. Therefore, proportional-integral-derivative (PID) controller is designed, we set Kp = 80, KI = 400, and KD = 0.7. The overshoot of the 1% step response is less than 10%, the steady state is attained in 0.5 s, and the steady-state error is no more than 2%, as shown in Figure 6(b).


Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

Lu F, Huang J, Xing Y - Sensors (Basel) (2012)

The response to step input by (a) PI controller with no delay; and (b) PID controller with delay.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472873&req=5

f6-sensors-12-11061: The response to step input by (a) PI controller with no delay; and (b) PID controller with delay.
Mentions: The control system should maintain the parameter ng to the reference under the gas turbine mode, for which proportional plus integral (PI) controller is used. When proportional gain Kp = 200 and integral gain KI = 600, the step response for a 1% step input under the steady state of ng% = 85% is shown in Figure 6(a). In order to discriminate and eliminate outliers, the sensed data ng is held for two time steps to determine the variances in Equations (14–16). If we still select PI controller, the control system will become unsteady. Therefore, proportional-integral-derivative (PID) controller is designed, we set Kp = 80, KI = 400, and KD = 0.7. The overshoot of the 1% step response is less than 10%, the steady state is attained in 0.5 s, and the steady-state error is no more than 2%, as shown in Figure 6(b).

Bottom Line: The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight.Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated.When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference.

View Article: PubMed Central - PubMed

Affiliation: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. lfaann@nuaa.edu.cn

ABSTRACT
Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

No MeSH data available.


Related in: MedlinePlus