Landing gear health assessment: synergising flight data analysis with theoretical prognostics in a hybrid assessment approach
| dc.contributor.author | El Mir, Haroun | |
| dc.contributor.author | King, Stephen | |
| dc.contributor.author | Skote, Martin | |
| dc.contributor.author | Alam, Mushfiqul | |
| dc.contributor.author | Place, Simon | |
| dc.date.accessioned | 2024-09-26T15:13:39Z | |
| dc.date.available | 2024-09-26T15:13:39Z | |
| dc.date.freetoread | 2024-09-26 | |
| dc.date.issued | 2024-06-27 | |
| dc.date.pubOnline | 2024-06-27 | |
| dc.description.abstract | This study addresses a critical shortfall in aircraft landing gear (LG) maintenance: the challenge of detecting degradation that necessitates intervention between scheduled maintenance intervals, particularly in the absence of hard landings. To address this issue, we introduce a Performance Degradation Metric (PDM) utilising Flight Data Recorder (FDR) output during the touchdown and initial roll phases of landing. This metric correlates time-series accelerometer data from a Saab 340B aircraft’s onboard sensors with non-linear response dynamic models that predict expected LG travel and reaction profiles across a set of ground contact cycles within a single landing. This facilitates the early detection of deviations from standard LG response behaviour, pinpointing potential performance abnormalities. The initiator of this approach is the Landing Sequence Typology, which systematically decomposes each aircraft landing into successive dynamic periods defined by their representative boundary conditions. What follows is the setting of initial parameters for the ordinary differential equations (ODE)s of motion that determine the orientation and impact responses of the most critical components of the LG assembly. Solving these ODEs with the integration of a non-linear representation of an oleo-pneumatic shock absorber model compliant with CS25 aircraft standards produces anticipated profiles of LG travel based on factors such as aircraft weight and speed at touchdown, which are subsequently cross-referenced with real accelerometer data, enhanced by video footage analysis. This footage is crucial for verifying the sequence of LG touchdowns and corresponding accelerometer outputs, thereby bolstering the precision of our analysis. Upon the conclusion of this study, by facilitating the early identification of LG performance deviations in specific landing scenarios, this diagnostic tool shall enable timely maintenance interventions. This proactive approach not only mitigates the risk of damage escalation to other components but also transitions main LG maintenance practices from reactive to proactive. | |
| dc.description.conferencename | PHM Society European Conference | |
| dc.description.journalName | PHM Society European Conference | |
| dc.format.extent | 583-592 | |
| dc.identifier.citation | El Mir H, King S, Skote M, et al., (2024) Landing gear health assessment: synergising flight data analysis with theoretical prognostics in a hybrid assessment approach. In: Proceedings of the PHM Society European Conference. PHM Society European Conference, 3 - 5 Jul 2024, Prague, Czech Republic, Volume 8, Issue 1, pp. 583-592, Article number 10 | |
| dc.identifier.eissn | 2325-016X | |
| dc.identifier.elementsID | 547778 | |
| dc.identifier.isbn | 978-1-936263-40-0 | |
| dc.identifier.issn | 2325-016X | |
| dc.identifier.issueNo | 1 | |
| dc.identifier.uri | https://doi.org/10.36001/phme.2024.v8i1.4085 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/22975 | |
| dc.identifier.volumeNo | 8 | |
| dc.language.iso | en | |
| dc.publisher | PHM Society | |
| dc.publisher.uri | https://papers.phmsociety.org/index.php/phme/article/view/4085 | |
| dc.rights | Attribution 3.0 Unported License | en |
| dc.rights.uri | https://creativecommons.org/licenses/by/3.0/ | |
| dc.subject | 40 Engineering | |
| dc.subject | 4001 Aerospace Engineering | |
| dc.subject | 4.2 Evaluation of markers and technologies | |
| dc.title | Landing gear health assessment: synergising flight data analysis with theoretical prognostics in a hybrid assessment approach | |
| dc.type | Conference paper | |
| dcterms.coverage | Prague, Czech Republic | |
| dcterms.dateAccepted | 2024-05-21 | |
| dcterms.temporal.endDate | 05-Jul-2024 | |
| dcterms.temporal.startDate | 03-Jul-2024 |