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Singular spectrum analysis is developed for the processing of nonlinear vibration measurements containing noise in structural damage detection. The method uses system augmentation to make the nonlinear system into an augmented linear system. The measured response of the system is decomposed and the corresponding decomposition subspace of the components which contains the least interference is reconstructed. Direct system parameter identification technique is then used to solve the model properties of the augmented system. Minimum rank perturbation theory is generalized so that it can be applied to detect local damage of the augmented system. Excellent identification results are obtained when Singular Spectrum Analysis (SSA) is applied, while identification result that without applying SSA shows large errors. The enhanced method is shown to be capable of yielding accurate identified results with noisy measurement in nonlinear systems.

The SEA model of hypersonic aircraft is established based on statistical energy analysis (SEA) theory. Three parameters of the SEA model are established by the theory and experiential formula. According to damping loss factors of model subsystem and acoustic absorptivity of cavity, sensitivity analysis of vibro-acoustic response is discussed. The effect that division way of plate subsystem and material structure cause to vibro-acoustic response is analyzed. The analysis results show that the material structure, damping loss factors and material type have the great effect on the characteristics of vibro-acoustic response. The division way of plate subsystem can affect computational accuracy greatly. The influencing factors should be synthetically considered in the design of acoustics structure.

An important part of the numerical simulation is the grid which the quality has great influence on the calculation precision, and also the influence often is crucial factor in most of situation. Water-entry at high speed is a complex unsteady process, and its numerical simulation needs to take consider of natural cavitation as well as rotation of the underwater body. In this paper, a new meshing method was given with using the Layering, Smoothing and Remeshing for calculating the unsteady flow field. Numerical simulation shows that the mesh given in this paper has better quality, and can be used to calculate the multi-phase mode of water-entry at the high speed.

Over decades phased array antenna technique attracts much more attention in Lamb wave based structural damage detection. Lamb wave generated by the piezoelectric wafers omnidirectionally could be steered at a specific direction during its propagation. Thus, the wave beam steering and focusing has been established, the location of structural damage is done with pulse-echo method by wave propagation. However, the detection accuracy will decrease as side bands energy leakage during wave propagation, so, signals to be generated have to be modified by window tone burst in order to concentrate energy in main bands and minimize the effect of dispersion side bands. In this paper, signals modified by Hanning-windowed tone burst was used to decrease the effect of side bands energy leakage, the results improved the detection accuracy better than signals without window tone burst and show good agreement with theoretical results. Meanwhile, A numerical simulation of aluminium plate demonstrates that phased array antenna technique is feasible in structural damage detection.

Bistable stochastic resonance is described by visual explanation. Engineering application feasibility of stochastic resonance is investigated, and the example of engineering application also given. Its application expectations are prospected.

Missiles always undergo non-stationary and continuously distributed load. However, only some centralized loads can be adopted in the ground for their vibration experiments. In this paper, the theoretical analysis and numerical simulation computations programs are established for the distributed and non-stationary airdynamic load being translated into several equivalent centralized loads for high-speed missile. The researches showed that, under the equivalent rule of structural modal responses, the average responses error in both domains time and frequency is within 1.5dB, so it is possible to provide a feasible method for the vibration test on the ground for missile structures.

A general approach for the online damage detection of laminated composite shells partially filled with fluid (LCSFF) is proposed in this paper. Based on advanced composite damage mechanics and the interaction between the fluid and the composite shell, a finite element (FE) model, is first established to simulate the structural response of LCSFF with damage. Piezoelectric patches are used as sensors and actuators to realize automatic damage detections in this FE model. The FE model is validated using structural natural frequencies obtained from experiments. The change in the energy spectrum of the decomposed wavelet signals of structural dynamic responses between the intact and damaged structures is used as the damage index due to its high sensitivity to the structural damage status. The non-linear mapping relationships between the structural damage index and various damage status of the LCSFF are established using an artificial neural network (ANN) trained with numerical structural dynamic response data. Results show that the general approach proposed in this paper can successfully identify the damage status of LCSFF with satisfactory accuracy.

A vibration-based damage detection method for a static laminated composite shell partially filled with fluid (LCSFF) is presented and validated by experiment. The crack damage is simulated using advanced composite damage mechanics in a dynamic finite element model, in which the interaction between the fluid and the composite shell is considered. The accuracy of FE model is first validated by comparing the computed and measured structural frequency response function. Structural damage indexes are constructed and calculated based on energy variation of the structural vibration responses decomposed using wavelet package before and after the occurrence of structural damage. An artificial neural network (ANN) is trained using numerically simulated structural damage index to establish the mapping relationship between the structural damage index and damage status. The test specimen used in experiment contains a cut in its surface made by laser cutting system. Response signals of both intact and damaged specimen are measured and used to construct the corresponding damage indices. The damage status is successfully identified using ANN, indicating that the method adopted in this paper can be applied to online structural damage detection and health monitoring for static LCSFF.

A method based on entropy-based criteria is present to choose the optimal decomposition of Wavelet Packets Analysis (WPA) for damage detection in composite materials. The structural damage indexes constructed based on energy spectrum variation of the structural vibration responses decomposed using WPA before and after the occurrence of structural damage usually generate a complete binary tree to calculate its elements. Date mining is carried out in this paper by adoption entropy as the criteria to choose the optimal decomposition tree. In the decomposition process, only the sub-signals which contain main information of the original signal are decomposed to generate next level sub-signals. New damage index is constructed based on the optimal decomposition. Then the dimension of the damage index is reduced while still keeping its sensitive to damage. Whether Artificial Neural Network (ANN) or genetic algorithm (GA) is used in the further process of telling structural damage status from damage index, this reduction will make remarkable time saving.

Sensor data are the basis for health assessment of complex structural systems. Careful selection and logical layout of sensors is critical to enable the high reliability of system health assessment. This paper presents a methodology how to use a minimum number of sensors, and what locations of them should be placed, so that the voltage signals received from the sensor can be used to detect both presence and extent of damage. In this study, an optimization procedure is developed using Genetic Algorithm (GA) to determine the location of piezoelectric sensor for damage detection in a composite wingbox. A new damage index using all differences in voltage signals decomposed by wavelet transform is proposed. Results show that the proposed method is available at determining number and location of sensors for structural damage detection using piezoelectric patch sensors.

The paper presents an effective damage detection method of complex composite structures. It can be carried out through the experimental modal analysis of the damaged structure. The method using the improved Cross Modal Strain Energy (CMSE) technique and Niche GA has many advantages compared with other damage detection methods. The CMSE method can use any modes of the structure and the modes don’t need to be normalized or consistent in scale. The Niche GA improves the efficiency of the calculation and enhances the capacity of identifying structural damage localization. The model is the composite material airfoil case. The numerical results show that the method proposed in this paper is successful for damage detection of complex structures.

A vibration-based approach to detect crack damage in a cantilever composite wingbox is studied using the improved Hilbert-Huang Transform (HHT). The improved HHT is composed of HHT with Wavelet Packet Transform (WPT) and a simple but effective method for intrinsic mode function (IMF) selection. For different damage status, in order to obtain structural dynamic responses, which imply plentiful damage information, the composite wing boxes were excited by a contrived square wave signal. Then, the dynamic responses of intact wingbox and damaged wingbox are disposed using improved HHT. Finally, a feature index vector of structural damage, i.e. the ariation quantity of instantaneous energy, is constructed. The obtained results show that the proposed damage feature index vector is more sensitive to small damage than those in traditional signal processing.

Many current methods on structural damage identification such as GA algorithms and neural networks technology are often implemented based on a few measured data and a large number of simulation data from structural vibration responses. Therefore, to establish an accurate and efficient dynamics model for a structure with different damage is an important precondition, so that plentiful simulation data of structural vibration response can be acquired using the dynamics model of the structure with damage. There are two problems when directly meshing small structural damage in FEM modeling, i.e., excessive gridding number and unavoidable errors from differently meshing for the same damaged structure. In order to solve these two problems, this paper presents an improved modeling method based on modifying element stiffness matrix at structural damage position using a modification coefficient. The first step of this improved modeling method is to determine modification coefficient of element stiffness matrix based on the coherence of natural frequencies for two kinds of models, and the second step is to verify the coherence of the frequency-response functions. This study also introduces algorithm and calculating results of damaged element stiffness matrix. Influence of structural damage position and constraint conditions on the modification coefficient for small structural damage are also discussed.