Affiliations: Naval Undersea Warfare Center, Division Newport,
Newport, RI 02841-1708, USA | NRC/Nondestructive Evaluation Sciences Branch, NASA
Langley Research Center, Langley, VA 23681, USA | Department of Mechanical Engineering, North Carolina
A&T State University, Greensboro, NC 27411, USA | Department of Mechanical Engineering, University of
Cincinnati, Cincinnati, OH 45221-0072
Abstract: A relatively overlooked factor in both global and local methods of
health monitoring is the nonlinear stiffness of structures caused by the
cycling of cracks and delaminations. Global methods of health monitoring use
modal parameters or frequency response functions in an inverse procedure to
quantify damage in structures with thick sections. Global approaches use fewer
sensors that detect only significantly large damage in structures due to damage
caused by transient vibration. However, local methods use Lamb wave propagation
to detect small damage within a structure by an array of closely spaced sensors
and actuators. Local methods also become more difficult to use on thick or
non-homogeneous materials because wave propagation becomes complex. This paper
develops a combined time series and wavelet analysis technique to improve
damage detection in either thick, complex geometry, or non-homogeneous
materials. A wavelet transmittance function (WTF) is defined as the ratio of
continuous wavelet transforms from the time responses at different locations on
a structure. A new damage indicator was developed based upon wavelet
transmittance function. The novelty of the method lies in the fact that a near
real time inference about the damage and the approximate extent of damage can
be drawn without historical data. A simulated model is illustrated to highlight
the potential of the new damage indicator on a thick aluminum specimen. Then,
experimental signal data from two sets of different experiments conducted on
thick structures with a crack and a delamination were analyzed using the
wavelet transmittance function to detect the presence and extent of the damages
as reflected on the WTF maps. This paper mainly deals with the development of
WTF and the associated damage indicator by analyzing the simulated and
experimental sets of data.
Keywords: health monitoring, thick materials, piezoceramic sensors, wavelet transmittance function
