Damage detection of engine bladed-disks using multivariate statistical analysis

X. Fang; J. Tang

doi:10.1117/12.658756

11 April 2006 Damage detection of engine bladed-disks using multivariate statistical analysis

X. Fang, J. Tang

Proceedings Volume 6174, Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems; 617429 (2006) https://doi.org/10.1117/12.658756
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2006, San Diego, California, United States

Abstract

The timely detection of damage in aero-engine bladed-disks is an extremely important and challenging research topic. Bladed-disks have high modal density and, particularly, their vibration responses are subject to significant uncertainties due to manufacturing tolerance (blade-to-blade difference or mistuning), operating condition change and sensor noise. In this study, we present a new methodology for the on-line damage detection of engine bladed-disks using their vibratory responses during spin-up or spin-down operations which can be measured by blade-tip-timing sensing technique. We apply a principle component analysis (PCA)-based approach for data compression, feature extraction, and denoising. The non-model based damage detection is achieved by analyzing the change between response features of the healthy structure and of the damaged one. We facilitate such comparison by incorporating the Hotelling's statistic T² analysis, which yields damage declaration with a given confidence level. The effectiveness of the method is demonstrated by case studies.

Citation Download Citation

X. Fang and J. Tang "Damage detection of engine bladed-disks using multivariate statistical analysis", Proc. SPIE 6174, Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, 617429 (11 April 2006); https://doi.org/10.1117/12.658756

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