Research On Impact Load And Damage Identification Techniques And Methods For Aircraft Structures

Recent developments in the area of smart materials and structures have made it possible to obtain the state of structure and to identify the structural safety status online with advanced actuator/sensor network integrated in the structure. It is important and crucial for impeding the structural degradation, increasing the flight safety and reducing the maintenance cost by applying structural heath monitoring system to obtain information about the characteristic, extent, distribution and progress of the damages.This dissertation studies several methods and techniques in structural health monitoring of aircraft structures. Both passive and active methods are applied to monitor the structure continuously and online to ensure the structural safety. These techniques can detect the impact events in/near real time, identify the impact location and reconstruct the impact force history, actively and quantitatively identify the damage location and damage size, and consider the effect of actual operational environment on damage detection and identification. After a brief introduction of the background of this study in Chapter 1, the main contents of this dissertation are as follows:(1) In Chapter 2, the impact identification problem for composite structure is studied. A general approach for impact load identification of composite structure, which can identify the impact location and reconstruct the impact force history simultaneously, is proposed. In the study, a simple and effective parameterization method is employed and the impact load is represented by a set of parameters, thus the impact localization in space domain and the force identification in time domain can be solved within the same algorithm. During the operation process, the impact load identification problem is transformed to a parameter optimization problem. Combining with a forward impact response model, intelligent optimization algorithm is employed to adaptively identify the impact location and time history by minimizing the difference between the computed model outputs and measured responses. Particularly, a micro-genetic algorithms (micro-GA) is employed as the intelligent optimization algorithm to perform the identification task with its global search capability and high computational efficacy. This new approach is simple and clear, each of the steps is independent and can be incorporated with different methods, providing a general and flexible approach for complex composite structures. Numerical simulation studies are performed to validate the effectiveness of the proposed method.(2) In Chapter 3, the problem of damage imaging using migration technique is studied. A frequency-wavenumber (f-k) migration technique is proposed for visualizing and identifying damages in plate-like structures, and improving the efficiency of damage identification. Based on Mindlin plate theory, the fast f-k migration method for dispersive flexural waves in isotropic plates is developed. The scattered and incident wavefields are extrapolated in f-k domain using Mindlin plate theory, respectively. Combined with the time-coincidence imaging condition, damages are actively imaged and identified by performing cross-correlation to the extrapolated scattered wavefield and incident wavefield. Then a new method for identifying the locations and initiation time of multiple simultaneous occurred damages in plate-like structure is proposed from the view of image processing. The f-k migration with the exploding imaging condition is employed to produce image displaying the locations of the damages by back-propagating the elastic waves emitted by the damages to their sources. An optimal criterion using minimum Shannon entropy is adopted to determine the image with the locations and initiation time of the damages mostly approximate the actual ones. Numerical simulation studies are performed to validate the effectiveness of the proposed methods.(3) In Chapter 4, the problem of damage detection and identification for composite structure under environmental changes is studied. A two-stage method is proposed to detect the existence of damage and identify the damage location with environmental effects. First a statistical outlier analysis method using Lamb waves is employed to detect the damage existence. To consider the environmental effect on damage detection, damage index is defined as the damage-sensitive feature from a statistical point. Outlier analysis is employed to process the damage index, and the damage threshold value to distinguish whether the change of Lamb wave signal is induced by damage in an actuator-sensor path or is only affected by environmental change is obtained by Monte Carlo approach. After the damage is detected, a damage presence probability imaging algorithm is used to fuse information collected from multiple actuator-sensor paths to form a diagnostic image to identify the damage. Damage index and its Mahalanobis square distance (MSD) are adopted as the damage features to generate the damage presence probability images, respectively. Experimental studies on a stiffened composite panel with temperature change are performed to demonstrate the effectiveness of the proposed method.This study is supported by the National Natural Science Foundation of China (No.10572058), the Research Fund for the Doctoral Program of Higher Education (No. 20050287016) and the Ph.D Innovation Foundation of NUAA (No. BCXJ07-03).