Conference Paper

Virtual sensor for fault detection and isolation in flight control systems - Fuzzy modeling approach

Delft University of Technology, Delft, South Holland, Netherlands
DOI: 10.1109/CDC.2000.914204 Conference: Decision and Control, 2000. Proceedings of the 39th IEEE Conference on, Volume: 3
Source: IEEE Xplore


A virtual sensor for normal acceleration has been developed and
implemented in the flight control system of a small commercial aircraft.
The inputs of the virtual sensor are the consolidated outputs of
dissimilar sensor signals. The virtual sensor is a fuzzy model of the
Takagi-Sugeno type and it has been identified from simulated data, using
a detailed, realistic Matlab/SimulinkTM model used by the
aircraft manufacturer. This virtual sensor can be applied to identify a
failed sensor in the case that only two real sensors are available and
even to detect a failure of the last available sensor

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    • "Sensor virtualization is another approach of programming the sensor that is by injecting fresh code into each node dynamically and changing its attributes, using this approach an error correction scheme is presented by reference [7]. Virtual Sensor Networks (VSN) middleware can also be based upon Fuzzy logic, as proposed by [8]. Network virtualization in WSN focuses on algorithms and protocol that links with the various underlying WSNs for the formation, merging, splitting, adding and deleting nodes as proposed in [9]. "
    Dataset: UTM Paper

    Full-text · Dataset · Nov 2014
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    • "Aircraft schematic and functional diagram of the aircraft model [22], [23]. the Takagi–Sugeno type for the identification of failed physical sensors, is presented in Oosterom and Babuska [17]. "
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    ABSTRACT: Aircraft sensors are important for proper operation and safety, and their condition is conventionally monitored based upon the hardware redundancy principle. In this work a statistical method capable of independently monitoring a single sensor, and thus enhancing reliability and overall system safety, is introduced. The method's main advantages are simplicity, applicability to a wide variety of aircraft operating conditions, the handling of uncertainties, no need for additionally monitored signals, and no need for physics based aircraft dynamics models. The method is based on a statistical time series framework accounting for random effects and uncertainties, and exploits the fact that abrupt faults are characterized by time constants smaller than those of the aircraft. It employs monitored signal nonstationarity removal, signal whitening via novel pooled autoregressive modeling, statistical decision making, as well as electronic spike/glitch removal logic. The method effectiveness is demonstrated within the simulation environment of a small commercial aircraft via test cases and Monte Carlo experiments with abrupt faults occurring in an angle-of-attack sensor.
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    • "Virtual sensors are presently used in many application areas, such as robotics, aerospace and marine technologies [6] [10] [20] [22]. The development of new robot systems, such as for seam tracking may be accelerated by the application of simulation. "
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