Structural damage detection using cross correlation functions of vibration response

Structural damage detection methods based on vibration responses are appealing for a variety of reasons such as their potential to observe damage from sensors placed remote from an unknown damage site. Of particular interest to the authors is online damage detection in which changes in the structure can be flagged up in an automated fashion by permanently installed transducers. In a previous paper by the authors, the inner product vector (IPV) was proposed as a damage detection algorithm which uses cross correlation functions between response measurements. Implicitly assumed in the formulation is that the response quantity is that of displacement resulting from white noise excitation. In this paper, the IPV technique is first reviewed and then generalised to address velocity and acceleration response to band pass white noise excitation. It is shown that the IPV is a weighted summation of the mode shapes, and the effect of some particular measurement noise on the IPV can be adaptively eliminated in the calculation of IPV. Then, the damage detection method based on changes in the IPV is proposed. Finally, damage detection experiments of shear frame structure, honeycomb sandwich composite beam and aircraft stiffened panel are presented to illustrate the feasibility and effectiveness of the proposed method.     

EXPERIMENTAL VALIDATION OF A STRUCTURAL HEALTH MONITORING METHODOLOGY: PART II. NOVELTY DETECTION ON A GNAT AIRCRAFT

This paper concerns the second phase of an experimental validation programme for a structural health monitoring methodology based on novelty detection. This phase seeks to apply one of the methods considered in the first stage of the work on a more realistic structure, namely the wing of a Gnat aircraft, as opposed to the previously investigated laboratory structure. The novelty detection algorithm used is that of outlier analysis and damage is introduced by making several copies of an inspection panel, each with a different controlled fault. All of these faults were detectable, a single feature was highlighted which proved capable of separating all the fault conditions from the unfaulted.     

The use of pseudo-faults for novelty detection in SHM

The main problem associated with pattern recognition based approaches to Structural Health Monitoring (SHM) is that damage localisation and quantification almost always require supervised learning. In the case of high-value engineering structures like aircraft, it is simply not possible to generate the training data associated with damage by experiment. It is also unlikely that data can always be generated by simulation as the models required would often need to be of such high fidelity that the costs of development and the run-times would again be prohibitive. The object of this paper is to explore the potential of a simple experimental strategy, which involves adding masses to the structure, in the attempt to extract features for novelty detection. The idea itself is not presented as revolutionary based on the fact that adding masses has been considered as a case of damage before, however, an in-depth investigation of its suitability for guiding feature selection is presented here. The approach is illustrated first on a simple structure by using data generated from a finite-element (FE) simulation and then validated experimentally on a more complicated laboratory structure. Simulated damage, in the form of a loss in the stiffness in the case of the numerical model and of a saw-cut in the case of the structure is used for comparison. The results show similar patterns in both cases which suggests a potential use of the method for higher level damage detection.     

Stochastic damage detection method for building structures with parametric uncertainties

Uncertainties, such as modeling errors and measurement errors, are inevitably involved in damage detection of a building structure. Most deterministic damage detection methods, however, do not consider uncertainties, thus limiting their practical application. A new stochastic damage detection method is therefore proposed in this paper for damage detection of building structures with parametric uncertainties. The proposed method contains two basic steps. The first step is to determine the probability density functions (PDFs) of the structural stiffness parameters before and after damage occurrence by integrating the statistical moment-based damage detection method with the probability density evolution method. In the second step, based on a special probability function calculated using the obtained PDFs, new damage indices are proposed and both damage locations and damage severities are identified. The feasibility and effectiveness of the proposed method are numerically demonstrated through a shear building structure with three damage scenarios. The first modal damping ratio of the building structure is regarded as a random parameter with a lognormal distribution. Numerical results show that both damage locations and damage severities can be identified satisfactorily. One of the advantages of the proposed method lies in that it can deal with uncertainty parameters of non-normal distributions.     

Health monitoring of a composite wingbox structure

This work was devoted to the development of a health monitoring system assigned to aerospace applications. Those applications concerned the detection of damaging impacts and debonding between stiffeners and composite skins, since they are the major causes of in-service damage of aircraft structures. The chosen health monitoring system was first based on the excitation and reception of Lamb waves along the structure by using thin piezoelectric transducers (active mode) and secondly on a continuous monitoring taking the same transducers used as acoustic emission sensors (passive mode). The composite specimen used was consistent with aircraft wingbox in terms of structure and loading. Several impacts with increasing energy increments were applied on the composite specimen. In passive mode, the study showed the ability of using the acoustic signature of an impact to detect possible damage. Moreover, the damage emergence in the case of damaging impact was confirmed in active mode. Further measurements during fatigue testing were performed. The aim was to demonstrate the ability of the system to monitor disbond growth between the stiffener and the composite skin. The sensitivity of the health monitoring system to the disbond growth was further demonstrated.     

基于BP神经网络的反潜巡逻机背景磁场补偿技术研究

通过分析反潜巡逻机背景磁场模型,针对传统模型求解时对模型参数求解方法存在的不足,本文提出了一种基于BP神经网络的飞机背景磁场模型求解新方法。该方法不讨论复杂的模型参数估计的问题,通过前期神经网络训练学习,直接把飞机磁补偿飞行过程中采集到的相关信号输入到训练好的网络中,得到输出干扰磁场,进而对其进行补偿。最后通过实例仿真验证了该方法的正确性和有效性,为提高反潜巡逻机磁探搜潜效能提供了科学依据,具有一定的军事意义。     

Damage detection of a rectangular plate by spatial wavelet based approach

This paper presents a technique for structure damage detection based on spatial wavelet analysis. Many damage detection methods require modal properties before and after damage. This method only needs the spatially distributed signals (e.g. the displacements or mode shapes) of the rectangular plate after damage. First, spatially distributed signals of the rectangular plate with damage are obtained by finite element method. The damaged region is represented as the elements with reduced stiffness. Then these spatially distributed signals are analyzed by wavelet transformation. It is observed that distributions of the wavelet coefficients can identify the damage position of rectangular plate by showing a peak at the position of the damage. It is also demonstrated that this method is very sensitivity to the damage size.     

基于一组Kalman滤波器信息融合的故障诊断

为了能及时准确地诊断发动机的传感器和执行机构故障,本文提出了基于一组Kalman滤波器信息融合的方法进行故障诊断。首先根据传感器特性设计了一组滤波器用于传感器故障诊断、隔离,每个滤波器针对一个传感器进行设计;其次根据执行机构故障特性设计了一组Kalman滤波器进行执行机构偏差估计,从而对执行机构进行故障诊断、隔离;接着给出了传感器、执行机构信息融合的诊断方案;最后分别给传感器、执行机构添加故障进行方案验证,仿真结果得出在传感器或者执行机构任意部件出故障的情况下,该融合方法可以有效地诊断并隔离出有故障的传感器或者执行机构。     

面向低空安全三维数字化空中走廊体系的飞行器交通管理平台构建

对低空空域的产业发展、低空飞行器的行业应用进行了阐述,对低空空域出现的潜在安全隐患进行了分析,开展了低空飞行器实时侦测和定位、实名认证准入制度、低空飞行器监测网构建研究,采用主动和被动式低空飞行器探测系统作为监测平台的补充模块,提出了面向低空安全三维数字化空中走廊体系的低空飞行器交通管理平台建设方案,为低空三维数字化空中走廊体系构建提供了关键技术支撑,对保障低空安全产业的健康、可持续性发展具有一定的参考价值。     

Combined damage detection techniques

Linear damage detection techniques are used frequently because of their simplicity and their easy interpretation. In this paper, it will be shown however that linear techniques are not very robust with respect to environmental changes and interstructure variability. With the aid of experimental results it will be demonstrated that non-linear damage detection techniques, although being more complex, are less sensitive to these effects. In addition, two damage detection approaches will be proposed that combine the advantages of different classes of techniques. Firstly, a combined linear-non-linear approach is described. In the second proposed method, static and dynamic measurement techniques will be combined. Using experimental damage detection results, it will be shown that both proposed combined techniques are less sensitive to environmental changes while leading to easy interpretation of results.     

Real-time aircraft noise likeness detector

One of the most difficult tasks involved in the process of noise monitoring near airports is related to the automatic detection and classification of aircraft noise events.These tasks can be solved by applying pattern recognition techniques to the audio signal captured by a microphone. But now the problem is caused by the background noise, which is present in real environments.This paper proposes a real-time method for continuously tracking the similarity of the input sound and the aircraft’s sounds. Using these facilities, the monitoring unit will be able to mark aircraft events, or to make measurements only when aircraft sound is louder than background noise.A one-class approach has been applied to this detection-by-classification method.Using the default setup, 93% of the aircraft’s events which held an SNR of 6-8 dB were detected, for 30 different locations with diverse soundscapes.     

Structural damage detection of controlled building structures using frequency response functions

If a building structure requires both a vibration control system and a health monitoring system, the integration of the two systems will be cost-effective and beneficial. One of the key problems of this integrated system is how to use control devices to enhance system identification and damage detection. This paper presents a new method for system identification and damage detection of controlled building structures equipped with semi-active friction dampers through model updating based on frequency response functions. The two states of the building are first created by adding a known stiffness using semi-active friction dampers. A scheme based on the frequency response functions of the two states of the building is then presented to identify stiffness parameters of structural members in consideration of structural connectivity and transformation information. By applying the proposed model updating scheme to the damaged building, a damage detection scheme is proposed based on the identified stiffness parameters of structural members of both the original and damaged buildings. The feasibility of the proposed schemes is finally demonstrated through a detailed numerical investigation in terms of an example building, in which the effects of measurement noise and excitation conditions are discussed. The numerical results clearly show that the proposed method can locate and quantify damage satisfactorily even though measurement noise is taken into consideration.     

Detection of osmotic damages in GRP boat hulls

Infrared thermography as a tool of non-destructive testing is method enabling visualization and estimation of structural anomalies and differences in structure’s topography. In presented paper problem of osmotic damage in submerged glass reinforced polymer structures is addressed. The osmotic damage can be detected by a simple humidity gauging, but for proper evaluation and estimation testing methods are restricted and hardly applicable. In this paper it is demonstrated that infrared thermography, based on estimation of heat wave propagation, can be used. Three methods are addressed; Pulsed thermography, Fast Fourier Transform and Continuous Morlet Wavelet. An additional image processing based on gradient approach is applied on all addressed methods. It is shown that the Continuous Morlet Wavelet is the most appropriate method for detection of osmotic damage.     

Thermo-acoustic fatigue characterization

The nondestructive detection of early fatigue damage states is of high importance for safety in aircraft, automobiles, railways, nuclear energy industries and chemical industries. Titanium alloys commonly used in aerospace for structures and engine components are subject to fatigue damage during service. In the current study fatigue damage progression in a titanium alloy (Ti-6Al-4V) was investigated using thermographic detection of the heat dissipated during short-term mechanical loading. The initial rate of temperature increase induced by the short-term mechanical loading was used to indicate the current microstructural state and presence of prior fatigue damage. Two methods for thermal excitation were investigated (a) high amplitude mechanical loading and (b) small amplitude ultrasonic loading. A formula that describes the temperature enhancement due to heat generation during one loading cycle is derived from high amplitude loading data. A correlation between the temperature increase during short-term ultrasonic loading and accumulated fatigue cycles is used to suggest a methodology for in-field assessment of fatigue condition.     

Structural damage evaluation using genetic algorithm

The detection and identification of structural damage is important in monitoring of structural systems during their lifetime. Many researchers have proposed a variety of damage evaluation methods based on structural monitoring. The stiffness matrix is used in some conventional damage detection methods; however, it leads to inevitable error due to the lack of data provided by structural monitoring. To overcome this problem, this study introduces a new damage evaluation method that identifies the structural damage in a shear building based on a genetic algorithm using the structural flexibility matrix with dynamic analyses. The proposed method enables the deduction of the extent and location of structural damage, even when there is insufficient data on the dynamic characteristics and insufficient accurate measurements of the structural stiffness and mass. The validity of the proposed damage evaluation method is demonstrated through numerical analyses using OpenSees.     

考虑太阳辐射影响的飞机实时红外探测成像仿真

针对飞行器红外探测过程的成像仿真,有助于红外隐身效能的评估,进而提高应对红外探测的反侦察能力。建立了飞机红外成像仿真模型,并针对不同的飞行姿态、速度以及不同的探测时间,求解其蒙皮温度与红外辐射亮度,结果表明当飞机从低速到高速运行时,太阳辐射条件与气动加热层温度分布分别成为影响其成像结果的主要因素。建模方法及仿真结果对飞行器的隐身设计具有指导意义,为飞机实时红外成像场景的生成提供理论基础     

Sensitivity analysis of an auto-correlation-function-based damage index and its application in structural damage detection

Structural damage detection using time domain vibration responses has advantages such as simplicity in calculation and no requirement of a finite element model, which attracts more and more researchers in recent years. In present paper, a new approach to detect the damage based on the auto correlation function is proposed. The maximum values of the auto correlation function of the vibration response signals from different measurement points are formulated as a vector called Auto Correlation Function at Maximum Point Value Vector, AMV for short. The relative change of the normalized AMV before and after damage is used as the damage index to locate the damage. Sensitivity analysis of the normalized AMV with respect to the local stiffness shows that the normalized AMV has a sharp change around the local stiffness change location, which means the normalized AMV is a good indicator to detect the damage even when the damage is very small. Stiffness reduction detection of a 12-story frame structure is provided to illustrate the validity, effectiveness and the anti-noise ability of the proposed method. Comparison of the normalized AMV and the other correlation-function-based damage detection method shows the normalized AMV has a better detectability.     

FRF-based damage localization method with noise suppression approach

In this paper a noise-robust damage identification method is presented for localization of structural damage in presence of heavy noise influences. The method works based on Frequency Response Functions (FRFs) of the damaged structure without any prior knowledge of the healthy state. The main innovation of this study starts with convolving FRFs with Gaussian kernel to suppress the noise. Denoised signals are then used to develop shape signals according to the second derivative of the operational mode shapes at frequencies in the half-power bandwidth of the center resonant frequencies. The scheme is followed by normalization of shape signals to create a two-dimensional map indicating the damage pattern. The validation of the method was carried out based on simulated data and experimental measurements. The simulated data polluted with 10 percent random noise considering four different conditions: (i) un-correlated noise with Gaussian distribution (ii) noise with non-Gaussian exponential distribution (iii) noise with non-Gaussian Log-normal distribution and (iv) correlated colored noise. The robustness of the method was examined with respect to the damage severity with various damage conditions. Finally, damage detection experiments of a fixed–fixed steel beam are presented to illustrate the feasibility and effectiveness of the proposed method. According to the numerical and experimental investigations, it was demonstrated that the proposed approach presents satisfactory damage indices both in single and multiple damage states in presence of high level noise. Hence, the method can overcome the problems of output measurement noise and deliver encouraging results on damage localization.     

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.     

基于分形理论的飞机雷击初始附着点的数值模拟

飞机雷击附着点的确定能够为飞机防雷设计提供依据,是飞机雷击区域划分和飞机各部件进行雷电试验鉴定的先决条件.本文提出了一种基于分形理论的飞机雷击初始附着点数值模拟的新方法.该方法首先依据标准SAE-ARP5416中有关飞机雷击附着点试验的规定,确定放电间隙、雷电起始坐标、飞机姿态和放电次数等参数,然后根据分形理论,使用电介质击穿模型模拟符合自然界雷电物理机理和几何特征的雷电先导分形发展过程,同时考虑飞机自身触发双向先导的情况,最终得到飞机的雷击附着点分布.通过本文方法仿真模拟得到飞机F-4雷击附着点的分布概率,并分别与该飞机飞行实验和实验室高压放电实验测试得到的真实雷击附着点的概率分布情况比较,结果基本吻合,验证了该方法的有效性.研究结果为飞机雷击附着点仿真模拟提供了一个有潜力的方法,可作为飞机防雷设计和今后开展相关研究工作的基础.