Grant A. Gordon

Optimal Estimation of Deterioration From Diagnostic Image Sequence

Estimation of mechanical structure damage can greatly benefit from the knowledge that the damage accumulates irreversibly over time. This paper formulates a problem of estimation of a pixel-wise monotonic increasing (or decreasing) time series of images from noisy blurred image data. Our formulation includes temporal monotonicity constraints and a spatial regularization penalty. We cast the estimation problem as a large-scale quadratic programming (QP) optimization and describe an efficient interior-point method for solving this problem. The method exploits the special structure of the QP and scales well to problems with more than a million of decision variables and constraints. The proposed estimation approach performs well for simulated data. We demonstrate an application of the approach to diagnostic images obtained in structural health monitoring experiments and show that it provides a good estimate of the damage accumulation trend while suppressing spatial and temporal noises.

Spatio-temporal filter for structural health monitoring

This paper considers the use of combined spatial and temporal filtering to improve the quality of a structural health monitoring (SHM) damage estimate. Many SHM systems produce two-dimensional (2-D) array data that contains structure damage estimate, which is distorted by noise from sensor sources, changing environmental conditions, and other inspection factors. We describe a filtering architecture for processing a sequence of damage estimates generated by a SHM system. We show that the approach can reduce the noise variability and enhance the damage estimate. The filter is designed as an infinite impulse response (IIR) filter in time and space and is predicated on an understanding of the point spread function for the ultrasonic interrogation. We discuss the basis for using a spatially invariant blurring operator to represent this interrogation process as well as the design of the filter. The filtering is performed in space by rejecting component of the input signal outside of the spatial frequency pass band. The filtering is also performed in time by rejecting the components of the signal outside of the dynamical pass band

Scattering of the Lowest Lamb Wave Modes by a Corrosion Pit

Scattering of time-harmonic Lamb wave modes by a partial spherical corrosion pit in a plate is investigated. By using superposition, the total field consists of the incident and scattered fields, where the latter is generated by tractions on the surface of the cavity. In the approximation advanced in this article these tractions are represented by time-harmonic body forces on a trace of the cavity in the interior of the plate. The acoustic radiation from the resultants of these body forces applied to the surface of the plate approximates the scattered field. The resultant forces are decomposed in symmetric and anti-symmetric systems, which generate symmetric and anti-symmetric radiating modes. The time-harmonic elastodynamic form of the reciprocity theorem is employed to obtain an analytical solution to the scattered field amplitudes. We obtain the ratio of scattered to incident Lamb mode amplitudes, which in a closed generalized form include material properties, geometry of the pit and layer, and angular frequency of the incident wave. Results of this study yield graphical representations for the amplitude ratios with respect to pit geometry and has the potential to lead to a unique solution of the inverse problem under some conditions.

Structural Damage Identification in a Mechanically Attached Metallic Panel Using Embedded Sensitivity Functions

A vibration-based structural damage identification method is discussed using experimental embedded sensitivity functions, which are algebraic combinations of measured frequency response functions (FRFs) that reflect changes in the response of mechanical systems when mass, damping, or stiffness parameters are changed. The theory of embedded sensitivity functions is reviewed and applied to identify damage in simulations with a six degree-of-freedom model of a metallic panel and in experiments on the actual panel. Measured FRFs, before and after simulated damage is imposed, are compared to an experimental sensitivity function. By matching the spectral shapes of these two sets of functions, damage is first located and classified as changes in stiffness, damping, or mass. Then the damage is quantified directly in engineering units as changes in stiffness or mass using only the measured data.

Quantitative corrosion monitoring and detection using ultrasonic Lamb waves

Corrosion is a major problem for airframe operators. For the aircraft industry in general, the direct costs of corrosion are estimated at

Structure health monitoring system and method

2.2 billion. As part of their strategy to control corrosion, airframe operators constantly seek to improve their ability to anticipate, manage and identify corrosion activity. Motivated by the need for an on-line real-time corrosion-monitoring tool for industry and aircraft a prototype system and analysis approach is presented. The tool employs ultrasonic Lamb waves along with a dispersion compensated synthetic aperture focusing technique (SAFT) to detect emerging pitting damage. In order to develop an automated detection approach the noise sources of the SAFT processed defect maps were examined and modeled. The random noise was found to be neither stationary nor normally distributed. Locally varying Weibull distribution parameters are used to characterize the image noise. An algorithm is developed to quantify the uncertainty in the corrosion detection and to allow assignment of a constant false alarm probability to any region of the monitored area.