ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Fuzzy-logic-based health monitoring and residual-life prediction for composite helicopter rotor

Pawar, Prashant M and Ganguli, Ranjan (2007) Fuzzy-logic-based health monitoring and residual-life prediction for composite helicopter rotor. In: Journal of Aircraft, 44 (3). pp. 981-995.

[img] PDF
PVJA26.pdf - Published Version
Restricted to Registered users only

Download (39kB) | Request a copy
Official URL: http://www.aiaa.org/content.cfm?pageid=318&volume=...


A health-monitoring and life-estimation strategy for composite rotor blades is developed in this work. The cross-sectional stiffness reduction obtained by physics-based models is expressed as a function of the life of the structure using a recent phenomenological damage model. This stiffness reduction is further used to study the behavior of measurable system parameters such as blade deflections, loads, and strains of a composite rotor blade in static analysis and forward flight. The simulated measurements are obtained using an aeroelastic analysis of the composite rotor blade based on the finite element in space and time with physics-based damage modes that are then linked to the life consumption of the blade. The model-based measurements are contaminated with noise to simulate real data. Genetic fuzzy systems are developed for global online prediction of physical damage and life consumption using displacement- and force-based measurement deviations between damaged and undamaged conditions. Furthermore, local online prediction of physical damage and life consumption is done using strains measured along the blade length. It is observed that the life consumption in the matrix-cracking zone is about 12-15% and life consumption in debonding/delamination zone is about 45-55% of the total life of the blade. It is also observed that the success rate of the genetic fuzzy systems depends upon the number of measurements, type of measurements and training, and the testing noise level. The genetic fuzzy systems work quite well with noisy data and are recommended for online structural health monitoring of composite helicopter rotor blades.

Item Type: Journal Article
Publication: Journal of Aircraft
Publisher: American Institute of Aeronautics and Astronautics
Additional Information: Copyright of this article belongs to American Institute of Aeronautics and Astronautics.
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 10 Jun 2010 10:28
Last Modified: 19 Sep 2010 05:57
URI: http://eprints.iisc.ac.in/id/eprint/26216

Actions (login required)

View Item View Item