Multiple input tangential interpolation-driven damage detection of a jet trainer aircraft

TL;DR

The paper tackles vibration-based SHM for full-airframe damage detection where direct modal-parameter comparisons are ambiguous in complex aeronautical structures. It proposes a two-step framework: identify modal parameters with the improved Loewner Framework (iLF) for MIMO data, then assess damage with the modified total modal assurance criterion (MTMAC) and localise with COMAC, under a linear time-invariant assumption. The approach is validated on a controlled numerical cantilever beam and on real full-scale Hawk T1A jet trainer data, demonstrating that iLF provides accurate modal extraction and MTMAC serves as a reliable damage index while COMAC aids localisation; these methods are benchmarked against LSCE and SSI-CVA. The work offers a computationally efficient, robust SHM solution for full-airframe damage detection with potential integration into digital twins and broader aerospace applications, while acknowledging thresholds are case-specific and requiring further validation across diverse structures.

Abstract

The problem of damage detection and identification is of interest for many aerospace and aeronautical engineering systems. However, relevant literature mostly focuses on subsystems and parts, rather than full airframes. In structural dynamics, modal parameters, such as natural frequencies and mode shapes, from any structure are the main building blocks of vibration-based damage detection. However, traditional comparisons of these parameters are often ambiguous in complex systems, complicating damage detection and assessment. The modified total modal assurance criterion (MTMAC), an index well-known in the field of finite element model updating, is extended to address this challenge and is proposed as an index for damage identification and severity assessment. To support the requirement for precise and robust modal identification of Structural Health Monitoring (SHM), the improved Loewner Framework (iLF), known for its reliability and computational performance, is pioneeringly employed within SHM. Since the MTMAC is proposed solely as a damage identification and severity assessment index, the coordinate modal assurance criterion (COMAC), also a well-established tool, but for damage localisation using mode shapes, is used for completeness. The iLF SHM capabilities are validated through comparisons with traditional methods, including least-squares complex exponential and stochastic subspace identification with canonical variate analysis on a numerical case study of a cantilever beam. Furthermore, the MTMAC is validated against the traditional vibration-based approach, which involves directly comparing natural frequencies and mode shapes. Finally, an experimental dataset from a BAE Systems Hawk T1A jet trainer ground vibration test is used to demonstrate the iLF and MTMAC capabilities on a real-life, real-size SHM problem, showing their effectiveness in detecting and assessing damage.

Figures (18)

• Figure 1: Numerical case study: schematic of the 2D beam with the dimensions of its hollow rectangular cross-section. Not in scale.
• Figure 2: Numerical case study: Stabilisation diagrams for the modes identified via iLF (\ref{['fig:fig2a']}), LSCE (\ref{['fig:fig2a']}), and SSI-CVA (\ref{['fig:fig2c']}) for the baseline scenario.
• Figure 3: Numerical case study: Difference between the iLF-identified $\omega_n$ of the baseline scenario and Cases #2-5.
• Figure 4: Numerical case study: $\bm{\phi}_n$ of the modes identified by iLF. Note that the secondary y-axis labels represent the dominant displacement shown.
• Figure 5: Numerical case study: Detailed view of $\bm{\phi}_{1,2}$ identified by iLF, showing the trajectory change according to the case number. Note that the secondary y-axis labels represent the dominant displacement shown.