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Failure management scheme for use in a flush air data system

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Failure management scheme for use in a flush air data system
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  Aircraft Design 4 (2001) 151–162 Failure management scheme for use in a flush air data system C.V. Srinatha Sastry a, *, K.S. Raman b , B. Lakshman Babu a,1 a Experimental Aerodynamics Di  v ision, National Aerospace Laboratories, Ban g alore 560 017, India b National Trisonic Aerodynamic Facilities, National Aerospace Laboratories, Ban g alore 560 017, India Abstract This paper concerns the development of a failure management software for use in a Flush Air DataSystem (FADS). FADS is used for the online computation of air data parameters namely, Mach number,angle of attack and angle of side slip. Failure management, an essential requirement for FADS, especiallyin the context of aircraft flight control applications, has been addressed using a novel concept called failureindicator vector. This new methodology ensures the selection of correct values out of a number of redundant values of a computed air data parameter. This method leads to symbolic processing techniques,which is found to be very effective in terms of programming efficiency and simple procedure for logicalreasoning. The method and the software have been successfully tested using the wind tunnel data generatedat NAL. r 2001 Published by Elsevier Science Ltd. 1. Introduction The online measurement of air data parameters, namely, the Mach number, angle of attack ( a )and angle of sideslip ( b ) of a flight vehicle is important as they provide input to flight controlfeedback systems, fire control systems, stall warning and terrain avoidance systems, etc. Hence,the instruments used to measure these parameters play a very crucial role in the flight control of an aircraft. Externally mounted conventional probe systems create additional drag and possibleflow disturbances around them. However, with the availability of online computing facilities, aFlush Air Data System (FADS), which computes critical air data parameters using orificepressure data and which does not have any protruding parts, is being seriously consideredcurrently in place of conventional probe systems. Following the successful use of nose cap andfuselage pressure orifices in the context of Shuttle orbiter, flush mounted air data sensors havebeen used in real time on YF-12 [1], Falcon-20, Rockwell B-2 bomber and Challenger CL-601aircraft [2]. This system is being evaluated on a modified F-18 [3,4]. A new adaptation of theFADS system is being developed for the X-33 single stage to orbit launch vehicle [5]. *Corresponding author. Fax: +91-80-527-3942. E-mail address:  sastry@ead.cmmacs.ernet.in (C.V. Srinatha Sastry). 1 Presently with Honeywell India Software Operations Pvt. Ltd., Bangalore.1369-8869/01/$-see front matter r 2001 Published by Elsevier Science Ltd.PII: S 13 6 9- 88 6 9 ( 0 1) 00 0 12 - X  Failure management is one of the most important factors for FADS. The FADS uses multipleorifice pressure data, which are measured using instruments like transducers and such other dataacquisition systems. This results in the computation of a large number of redundant values of output parameters. In the failure condition, some of the orifices may be blocked or some of thesensors or other data acquisition instruments may fail to function, resulting in erroneous values of computed air data parameters, corresponding to the erroneous pressure values. Many attemptshave been made to address the failure management problems arising out of measurementuncertainty [3,6] and to develop fault tolerant algorithms for flush air data system [7]. These areaimed at evaluating the effects of various error sources on the overall uncertainty using errorsimulation and statistical error estimation methods. Neural network methods have been used todetect and compensate for lost input signals [7].However, in an online situation, the immediate need would be to compare judiciously theredundant air data values, identify the erroneous values and discard the same and moreimportantly provide accurate air data, without worrying about the nature and sources of failure of some of these redundant values. Further, in such complex situations, this task should be achievedwithout human intervention, by evolving a computational procedure. Any software developed forthis purpose has to incorporate a large number of inputs, use efficient algorithms with high levelreasoning and quick decision making procedures, which are qualitative in nature with simplecomputational procedures for immediate solutions.In this paper, a  no v el concept  for failure management has been introduced in the context of determining critical air data parameters for a typical FADS. The method is based on voting logicand symbolic reasoning, which will enable to take decisions quickly in the multiple and redundantparameter environment. The methodology used has been successfully demonstrated by simulatingcertain errors in the input data. 2. Flush air data system The FADS system consists of orifices flush on the surface of the nose cone of the aircraft. Multi-flush orifices are used to take care of the redundancy requirements. A cone cylinder model with Nomenclature a  angle of attack b  angle of side slip q  dynamic pressure P i   pressure at the orifice number  i  D P a  differential pressure across an orifice pair P t  stagnation pressure measured in wind tunnel P ti   stagnation pressure at the orifice number  i  D P t  = P t    P e  threshold value used for air data parameters C.V. Srinatha Sastry et al. / Aircraft Design 4 (2001) 151–162 152  a hemispherical nose whose included angle is 30 1  was used for the present study. A total numberof 27 pressure orifices were located on the nose cone as shown in Fig. 1. Orifices 1–7 are locatedvertically in the nose cap. They are sensitive to the change in angle of attack while the orifices 8–11located horizontally are sensitive to angle of sideslip. The orifices located at the center of the nosecap (orifice 4) and adjacent to it (orifices 3 and 5) are used to get the stagnation pressure while theorifices 12–27 located on the nose cone aft of the hemispherical region are considered for sensingthe static pressure (Fig. 2). 2.1. Computation of air data  v alues The nose cone model was calibrated in the NAL 0.6m Transonic wind tunnel. Measurementswere made in the Mach number range 0.3–1.2 in steps of 0.1. Orifice pressures were measured by Fig. 1. Schematic of flush air data orifices on the nose cone model.Fig. 2. Flush office numbering. C.V. Srinatha Sastry et al. / Aircraft Design 4 (2001) 151–162  153  two 7 10psid ESP scanners having 16 ports each. The model was pitched from   10 1  to +18 1  instep mode with 2 1  increments during each run. Measurements at some Mach numbers wererepeated to check data repeatability.The software for FADS includes development of appropriate interpolation and curve fittingmodules for the generation of calibration data from wind tunnel tests. This database and the well-known relationships between the roll angle, pitch angle, angle of attack and side slip angle wouldthen be used for the computation of the air data (Mach number, angle of attack and side slipangle). An iterative data reduction procedure for determining air data using orifice pressure datawas validated using the space shuttle orbiter FADS model data [8]. The method requires one set of calibration data generated in a wind tunnel measuring pressures of a pair of orifices locateddiametrically opposite to each other on either side of the center port (stagnation pressure port)and the stagnation pressure values. This data base, along with the instantaneous pressure valuesof the same orifice pair and the stagnation pressure in flight are used to compute the air data.However, such sets of calibration data with respect to various pairs of orifices and theinstantaneous pressure values of the corresponding orifice pairs are used to compute the same airdata, for the purpose of redundancy.The calibration curves representing the difference between the wind tunnel stagnation pressureand the stagnation pressure at the nose, normalised with respect to the stagnation pressure at theorifice number 4, are used to estimate the dynamic pressure. Further, the calibration curves of normalized differential pressure across pairs of orifices ( D P a = q ;  the ratio of orifice pair differentialpressure to the dynamic pressure) for various pitch angles and for various Mach numbers, areused to compute the angle of attack. The iterative method also uses a third group of calibrationcurves being the ratios of the same orifice pair pressure values, to derive the Mach number. Threegroups of calibration curves with respect to the stagnation pressure port number 4 and the pair of orifices 1 and 7 are shown in Figs 3–5. -0.0500.050.10.150.20.25-10 -5 0 5 10 15 20   (deg.)         P      t      i      /      P      t      i M=0.3M=0.4M=0.5M=0.6M=0.7M=0.8M=0.9M=1.0M=1.1M=1.2 Fig. 3. Calibration curve used to estimate the dynamic pressure. C.V. Srinatha Sastry et al. / Aircraft Design 4 (2001) 151–162 154
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