A fuzzy logic system for ground based structural health monitoring of a helicopter rotor using modal data

A fuzzy logic system (FLS) is developed for ground based health monitoring of a helicopter rotor blade. Structural damage is modeled as a loss of stiffness at the damaged location that can result from delamination. Composite materials, which are widely used for fabricating rotor blades, are susceptible to such delaminations from barely visible impact damage. The rotor blade is modeled as an elastic beam undergoing transverse (flap) and in-plane (lag) bending, axial and torsion deformations. A finite element model of the rotor blade is used to calculate the change in blade frequencies (both rotating and nonrotating) because of structural damage. The measurements used for health monitoring are the first four flap (transverse bending) frequencies of the rotor blade. The measurement deviations due to damage are then fuzzified and mapped to a set of faults using a fuzzy logic system. The output faults of the fuzzy logic system are four levels of damage (undamaged, slight, moderate and severe) at five locations along the blade (root, inboard, center, outboard, tip). Numerical results with noisy data show that the FLS detects damage with an accuracy of 100% for noise levels below 15% when nonrotating frequencies are used. The FLS also correctly classifies the "undamaged" condition up to noise levels of 30% thereby reducing the possibility of false alarms, a key problem for diagnostics systems. The fuzzy logic approach is thus able to extract maximum information from very limited and uncertain data. Using rotating frequencies lowers the success rate for small damage because the centrifugal stiffening caused by rotation counters the stiffness reduction caused by structural damage. The fuzzy logic system in this study is proposed as an information-processing tool to help the maintenance engineer by locating the damage area roughly but accurately for further nondestructive inspections.