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Normalised Diagnostic Contribution Index (NDCI) Integration to Multi Objective Sensor Optimisation Framework

Burak Suslu1, Fakhre Ali1, Ian K Jennions1

  • 1Integrated Vehicle Health Management Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.

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Summary
This summary is machine-generated.

This study introduces the Normalised Diagnostic Contribution Index (NDCI) into a sensor optimisation framework for aerospace systems. The enhanced approach improves diagnostic efficiency and sensor selection for stakeholders like airlines and MROs.

Keywords:
aircraftcomplex systemsdiagnosticsenvironmental control systemshealth managementmulti-objective sensor optimisationnormalised diagnostic contribution index

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Area of Science:

  • Aerospace Engineering
  • Systems Engineering
  • Data Science

Background:

  • Effective sensor optimisation is crucial for diagnostics, resource management, and maintenance in aerospace.
  • Existing methods may not fully address application-specific needs or diverse stakeholder requirements.

Purpose of the Study:

  • To integrate the Normalised Diagnostic Contribution Index (NDCI) into the Multi-Objective Sensor Optimisation Framework (MOSOF).
  • To enhance sensor optimisation for aerospace systems, considering multiple stakeholder perspectives (OEM, Airlines, MRO).
  • To improve diagnostic efficiency and reduce sensor redundancy through a novel optimisation approach.

Main Methods:

  • Utilised a multi-objective genetic algorithm within the MOSOF.
  • Derived NDCI from simulation data of a Boeing 737-800 Environmental Control System (ECS) using the SESAC platform.
  • Analysed sensor performance across four fault modes and evaluated against the Minimum Redundancy Maximum Relevance (mRMR) method.

Main Results:

  • The NDCI-MOSOF identified an optimal set of three sensors, outperforming mRMR's six-sensor solution.
  • Demonstrated significant improvements in diagnostic efficiency for all stakeholders.
  • Expanded the solution space for sensor configurations, prioritising diagnostic value over mere redundancy.

Conclusions:

  • The enhanced NDCI-MOSOF provides a scalable, multi-stakeholder solution for next-generation sensor optimisation.
  • This approach is vital for advancing predictive maintenance in complex aerospace systems.
  • The integration offers a distinct advantage in identifying optimal sensor sets tailored to specific diagnostic needs.