Drift fault accommodation system of a transport aircraft using Neural Network models

Singh, Seema; S, Shashank; Hegde, Shrisha S; Paul, Tapas Kumar; Reddy, R. L. N.

doi:10.1109/icacci.2018.8554748

Cited by 3 publications

(1 citation statement)

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“…The equation used for the induction of a drift fault is given as [ 14 ]

where Y , s , t , d , and U are the sensor outputs with fault, slope, simulation time, time at which fault is induced, and fault-free sensor value, respectively. The slope values used for the current study are −0.20, 0.20, and −0.10.…”

Section: Fdi Techniques Applied To Orifice Flowmetermentioning

confidence: 99%

Detection of Sensor Faults with or without Disturbance Using Analytical Redundancy Methods: An Application to Orifice Flowmeter

Sravani

Venkata

2023

Sensors

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Sensors and transducers play a vital role in the productivity of any industry. A sensor that is frequently used in industries to monitor flow is an orifice flowmeter. In certain instances, faults can occur in the flowmeter, hindering the operation of other dependent systems. Hence, the present study determines the occurrence of faults in the flowmeter with a model-based approach. To do this, the model of the system is developed from the transient data obtained from computational fluid dynamics. This second-order transfer function is further used for the development of linear-parameter-varying observers, which generates the residue for fault detection. With or without disturbance, the suggested method is capable of effectively isolating drift, open-circuit, and short-circuit defects in the orifice flowmeter. The outcomes of the LPV observer are compared with those of a neural network. The open- and short-circuit faults are traced within 1 s, whereas the minimum time duration for the detection of a drift fault is 5.2 s and the maximum time is 20 s for different combinations of threshold and slope.

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“…The equation used for the induction of a drift fault is given as [ 14 ]

Section: Fdi Techniques Applied To Orifice Flowmetermentioning

confidence: 99%