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Upset detection for passenger airliners using classification of anemometric and inertial sensor data
Thesis (MEng)--Stellenbosch University, 2016.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2016
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| _version_ | 1867614024521220096 |
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| access_status_str | Open Access |
| author | Malan, Pieter Jacobus |
| author2 | Engelbrecht, J. A. A. |
| author_browse | Engelbrecht, J. A. A. Malan, Pieter Jacobus |
| author_facet | Engelbrecht, J. A. A. Malan, Pieter Jacobus |
| author_sort | Malan, Pieter Jacobus |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2016. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/100173 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:45:27.799Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/100173 Upset detection for passenger airliners using classification of anemometric and inertial sensor data Malan, Pieter Jacobus Engelbrecht, J. A. A. Engelbrecht, H. A. Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Passengers, Airplane -- Safety Signal detection Aeronautics, Commercial Fault tolerance (Engineering) Control systems (Flight) UCTD Thesis (MEng)--Stellenbosch University, 2016. ENGLISH ABSTRACT: Due to the increasing number of civilians making use of airliners for business and travel purposes, safe and reliable operation of commercial passenger airliners is essential. Aircraft upsets are particular conditions that may result in fatal accidents. The accurate identification of such upsets, however, can greatly reduce the risk of fatal accidents. Conventional flight control systems for aircraft are designed to operate within a specified flight envelope, which is defined by an allowable range of air incidence angles (called the angle of attack and side-slip angle), airspeeds, and angular rates over which the aerodynamic forces and moments behave linearly. The flight envelope is also defined by an allowable range of aircraft attitudes (pitch angles and bank angles) and flight trajectories. When the aircraft exceeds its flight envelope, it enters the upset domain, where the aircraft typically stalls and may enter an uncontrolled spin. A need therefore exists for a system that can detect and recognise “out-of-envelope” conditions using on-board sensor measurements. Pilots are not always aware that the aircraft has entered the upset domain, especially if visual cues are not available, and may respond with incorrect actions. It is however possible for a pilot to recover from an upset event, but the knowledge of the specific upset event is of utmost importance. A need therefore exists to advise the pilot of an occurring upset so that the correct recovery actions can be taken. This thesis presents the design and verification of an upset detection system for commercial passenger airliners that detects and identifies flight upset conditions using classification techniques operating on sensor data from on-board anemometric and inertial sensors. The study focused on three aerodynamic upsets, namely high angle of attack upset, underspeed upset and a novel predictive form of high angle of attack upset detection named dynamic pitch upset. The upset detection system used classification algorithms trained on labelled anemometric and/or inertial sensor measurements. A wide variety of classifiers were investigated in order to determine the feasibility of classification-based upset detection. The three aerodynamic upset detection systems were evaluated across two cases, namely those that utilised sensor data from both the anemometric and inertial sensors, and those using data from only the inertial sensors. The high angle of attack upset detection system provided an accuracy of 98.8% for initial test case and an accuracy of 92.2% for the latter. The underspeed upset detection system provided an accuracy of 99.3% for the first case and 89.4% for the second case. The dynamic pitch upset detection system provided an accuracy of 93.6% for the initial case and 91.4% for the latter. The high classifier accuracies provided a suitable and reliable means for aircraft upset detection. These accuracies, along with the locations of the false alarms—the false alarms occur near the upset boundary—enable the pilots to detect and recognise instances pertaining to upset. AFRIKAANSE OPSOMMING: Die toenemende aantal individue wat gebruik maak van lugvaart noodsaak onbetwisbare betroubaarheid van kommersi¨ele-passasier-vliegtuie. Noodlottige vlug ongelukke mag die gevolg van ’n buite vlugbestek toestand wees. Die akkurate identifisering van hierdie buite vlugbestek toestande mag ’n noemenswaardige vermindering in noodlottige ongelukke teweegbring. Konvensionele vlug-beheerstelsels is ontwerp om binne ’n vasgestelde vlugbestek te funksioneer. Hierdie vlugbestek word gedefinieer as die toelaatbare reeks lugvloei-invalshoeke, lugspoed-intervalle en hoek-tempos waarin die a¨erodinamiese-kragte en -momente lineˆer reageer. Die vlugbestek word ook deur die toelaatbare reeks vliegtuig-ori¨entasies en vlugtrajekte bepaal. Indien die vliegtuig die vlugbestek verlaat, betree dit ’n buite vlugbestek toestand, waar die vliegtuig mag staak en onbeheerd-tol. ’n Stelsel wat buite vlugbestek toestande kan identifiseer deur gebruik te maak van beskikbare sensore word dus genoodsaak. Vlie¨eniers mag soms nie bewus wees van ’n buite vlugbestek toestand nie, en mag gevolglik met die verkeerde dade reageer. Dit is moontlik om vanuit ’n buite vlugbestek toestand te herstel, maar die kennis van die spesifieke buite vlugbestek toestand is krities in di´e verband. ’n Stelsel wat die vlie¨enier inlig van ’n buite vlugbestek toestand sodat die nodige maatre¨els gevolg kan word, is dus van uiterste belang. Die ontwerp en verifikasie van ’n buite vlugbestek opsporingstelsel vir kommersi¨ele vliegtuie deur die klassifisering van beskikbare sensor metings, word in hierdie tesis aangebied. Drie verskillende buite vlugbestek toestande, naamlik ho¨e-aanvalshoek, laespoed en dinamiese-hellingshoek was ondersoek. Die klassifikasie-algoritmes wat ondersoek is, is afgerig op gemerkte anemometries- en inersi¨ele-sensor lesings. ’n Wye verskeidenheid van klassifikasie-algoritmes was ondersoek om die vermo¨e daarvan as buite vlugbestek opsporingstelsel te bepaal. Twee gevalle per buite vlugbestek toestand was ondersoek, naamlik anemometries- en inerisi¨ele-sensore beskikbaar, en slegs inersi¨ele-sensore beskikbaar. Die ho¨e-aanvalshoekopsporingstelsel het akkuraathede van 98.8% en 92.2% vir die twee gevalle onderskeidelik behaal. Die laespoed-opsporingstelsel het akkuraathede 99.3% en 93.6% vir die twee gevalle onderskeidelik behaal. Die dinamiese-hellingshoek-opsporingstelse het akkuraathede van 93.6% en 91.4% vir die twee gevalle onderskeidelik behaal. Die ho¨e akkuraatheid van die stelsels het bygedra tot meer betroubare buite vlugbestek opsporing. Hierdie akkuraathede, gepaard met die posisies van die vals-alarms, (valsalarms het plaasgevind naby die grens van buite vlugbestek), bemagtig vlie¨eniers om buite vlugbestek toestande beter te identifiseer. 2016-12-22T13:23:23Z 2016-12-22T13:23:23Z 2016-12 Thesis http://hdl.handle.net/10019.1/100173 en_ZA Stellenbosch University 180 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Passengers, Airplane -- Safety Signal detection Aeronautics, Commercial Fault tolerance (Engineering) Control systems (Flight) UCTD Malan, Pieter Jacobus Upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| title | Upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| title_full | Upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| title_fullStr | Upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| title_full_unstemmed | Upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| title_short | Upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| title_sort | upset detection for passenger airliners using classification of anemometric and inertial sensor data |
| topic | Passengers, Airplane -- Safety Signal detection Aeronautics, Commercial Fault tolerance (Engineering) Control systems (Flight) UCTD |
| url | http://hdl.handle.net/10019.1/100173 |
| work_keys_str_mv | AT malanpieterjacobus upsetdetectionforpassengerairlinersusingclassificationofanemometricandinertialsensordata |