Advances in Prognostics and Health Management for Aircraft Landing Gear—Progress, Challenges, and Future Possibilities

Izaz Raouf, Prashant Kumar, Yubin Cheon, Mohad Tanveer, Soo Ho Jo, Heung Soo Kim

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

Prognostics and health management (PHM) has developed into a crucial discipline because of its never-ending pursuit of safety, effectiveness, and dependability. The aircraft Landing gear (LG) is one of the most significant components during takeoff and landing. Consequently, the PHM of LG is essential for the aircraft to operate safely and reliably. This paper provides an in-depth exploration of the developments, difficulties, and prospects in PHM for aircraft LG. The study begins by providing an overview of the LG parts and related faults, emphasizing their importance for the flight safety. The insights of PHM are presented based on various artificial intelligence (AI) techniques. Various approaches are discussed for fault detection and isolation (FDI) and remaining useful life (RUL). These efforts help to improve the maintenance and decision-making (MDM) process, which improves the overall effectiveness of PHM. With the aim of giving researchers a useful resource, this review addresses to fill the research gaps based on the available literature so far. It lays the foundations for future advancements by highlighting the challenges in this field.

Original languageEnglish
Article number107126
Pages (from-to)301-320
Number of pages20
JournalInternational Journal of Precision Engineering and Manufacturing - Green Technology
Volume12
Issue number1
DOIs
StatePublished - Jan 2025

Keywords

  • Aircraft maintenance
  • Fault detection
  • Landing gear PHM
  • Maintenance decision-making
  • RUL prediction

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