Damage detection in repairs using frequency response techniques

Structural health monitoring (SHM) technology may be applied to composite bonded repairs to enable the continuous through-life assessment of the repair’s efficacy. Adhesively bonded joints are an ideal starting point for real-time, in situ monitoring due to known mechanisms and locations of failure. Similarly, the ability to accurately monitor the health of a joint has potential to aid acceptance of adhesive bonding. This paper describes the development of an SHM technique for the detection of debonding in composite bonded patches based on frequency response. Two commonly used repair schemes, the external doubler repair and the scarf repair, are examined. The paper outlines an experimental investigation on the frequency response of the repairs with and without defects under different boundary conditions. It was found that damage could be readily detected through changes in frequency response for both types of repair. The results are discussed with implications for the development of a technology to monitor the integrity of composite bonded repairs.     

Damage detection in beams from modal and wavelet analysis using a stationary roving mass and noise estimation

This paper uses the Continuous Wavelet Transform Analysis on mode shapes for damage identification. The wavelet analysis is applied to the difference in the mode shapes between a healthy and a damaged state. The paper also includes a novel methodology for estimating the level of noise of the experimental mode shapes based on a standard Signal to Noise Ratio (SNR). The estimated SNRs are used for identifying and making emphasis on the less noisy data. Moreover, a mass attached to the structure is considered to enhance the sensitivity of the structure to damage. Modal analysis is performed for different positions of the mass along the beam. The results obtained for all the positions of the mass are combined so an averaging process is implicitly applied. The paper presents the results from an experimental test of a cantilever steel beam with different severity levels of damage at the same location. The results show that the use of the attached mass reduces the effect of noise and increases the sensitivity to damage. Little damage can be identified with the proposed methodology even using a small number of sensors and only the first five bending modes.     

Distributed parameter thermal system control and observation by Green–Galerkin methods

This article addresses the problem of distributed parameter control and observation in thermal processing of materials. A novel numerical technique is developed for infinite‐dimensional thermal conduction systems, based on Galerkin optimization of an energy index employing Green's functions. Various simulations are conducted to prove that despite the complexities that arise from the distributed parameter nature of the system, the proposed method successfully observes the temperature field that exists inside a solid body by employing strictly surface temperature measurements. Moreover, the existence of a duality principle between distributed parameter thermal control and thermal observation is also investigated. Copyright © 2004 John Wiley & Sons, Ltd.     

Micro- and Macroscale Damage Detection Using the Nonlinear Acoustic Vibro-Modulation Technique

Subjected to in-service and environmental loads, even relatively new structural components may reveal signs of microscopic deterioration. Very often, this initial damage further progresses into meso- and macroscales leading to development of one or several macrocracks that cause ultimate structural failure. Although the onset of macroscale cracking can be reliably detected by modern NDE methodologies, there is an increasing need for inspection technologies that may allow for assessing structural damage at a wide range of scales, i.e., from micro to macro. This article explores application of the nonlinear acoustic vibro-modulation technique (VMT) to incipient damage detection and monitoring. The nonlinear acoustic detection of the macroscopic damage is illustrated with examples: inspection of the cast aluminum automotive parts and testing of the aging aircraft fuselage. The microscale damage assessment is realized by real-time monitoring of the acoustic nonlinearity in the strain controlled three-point-bending fatigue test. In the experiment, a stable increase of the nonlinear response during specimen fatigue was observed indicating early damage accumulation before the macroscopic fracture.     

北京地区山背波监测与特征分析

利用北京西北地区布置的小孔径大气次声传感器网络,利用有效来波判断方法搜寻有效来波,并使用最小方差空间搜索方法定位波源,分析经常发生并对正常观测造成干扰的一种次声波—山背波信号的特征规律:幅度、频谱、波源位置、波速、来波方向及发生时间统计规律。对2013年4~5月的次声波记录数据进行分析,结果显示:低于0.02 Hz频段,各传感器经常性接收到来自于西北山区方位的次声波,幅度一般在10~20 Pa,中心频率处于0.002~0.005 Hz,最小方差法定位结果显示信号源大多自北京西山的面向阵列的一侧,方位角统计结果显示大多数在260°~360°、0°~40°,且传播速度为10~50 m/s,该波的发生与当地的风速风向具有相关性。     

Modeling and Monitoring Ecological Systems—A Statistical Process Control Approach

Statistical process control monitoring of nonlinear relationships (profiles) has been the subject of much research recently. While attention is primarily given to the statistical aspects of the monitoring techniques, little effort has been devoted to developing a general modeling approach that would introduce ‘uniformity of practice’ in modeling nonlinear profiles (analogously with the three‐sigma limits of Shewhart control charts). In this article, we use response modeling methodology (RMM) to demonstrate implementation of this approach to statistical process control monitoring of ecological relationships. Using 10 ecological models that have appeared in the literature, it is first shown that RMM models can replace (approximate) current ecological models with negligible loss in accuracy. Computer simulation is then used to demonstrate that estimated RMM models and estimated data generating ecological models achieve goodness‐of‐fit that is practically indistinguishable from one another. A regression‐adjusted control scheme, based on control charts for the predicted median and for residuals variation, is developed and demonstrated for three types of ‘out of control’ scenarios. Copyright © 2013 John Wiley & Sons, Ltd.     

Detection and classification mean-shifts in multi-attribute processes by artificial neural networks

To monitor the quality of a multi-attribute process, some issues arise. One of them being the occurrence of a high number of false alarms (type I error) and the other an increase in the probability of not detecting defects when the process is monitored by a set of independent uni-attribute control charts. In this paper, based upon the artificial neural network capabilities we develop a new methodology to overcome this problem. We design a perceptron neural network to monitor either the proportions of several types of product nonconformities (instead of using several np charts) or the number of different types of defects (instead of using several c charts) in a product. Moreover, while the proposed method possesses the ability to be applied for small sample sizes, it is also able to diagnose the mean shift online. We present two simulation experiments in which the proportions of several types of nonconformities are monitored. In addition, we present one more simulation experiment in which the number of different types of defect is controlled. We also compare the performance of the proposed methodology with the ones from the Mnp and T ² charts for multi-attribute processes. The results of the simulation studies are encouraging.     

Carbon Nanotubes Multifunctionalized by Rolling Circle Amplification and Their Application for Highly Sensitive Detection of Cancer Markers

There are still challenges for the development of multifunctional carbon nanotubes (CNTs). Here, a multiwalled carbon nanotube (MWCNT)‐based rolling circle amplification system (CRCAS) is reported which allows in situ rolling circle replication of DNA primer on the surface of MWCNTs to create a long single‐strand DNA (ssDNA) where a large number of nanoparticles or proteins could be loaded, forming a nano‐biohybridized 3D structure with a powerful signal amplification ability. In this strategy, the binding ability of proteins, hybridization, replication ability of DNA, and the catalytical ability of enzymes are integrated on a single carbon nanotube. The CRCAS is then used to develop colorimetric and chemiluminescent assays for the highly sensitive and specific detection of cancer protein markers, alpha‐fetoprotein (AFP) and prostate specific antigen (PSA). The colorimetric CRCAS assay is 4000 times more sensitive than a conventional enzyme‐linked immunosorbent assay (ELISA), and its concentration range is 10 000 times wider. Control experiments show that as low as 10 pg mL^?1 AFP or PSA could be detected even in the presence of interfering protein markers with a more than 10⁵‐fold greater concentration in the sample, demonstrating the high specificity of the CRCAS assay. The limit of detection of the chemiluminescent CRCAS assays for AFP and PSA are 5 fg mL^?1 (70 aM) and 10 fg mL^?1 (0.29 fM), respectively, indicating that the sensitivity is much higher than that of the colorimetric CRCAS assay. Importantly, CRCAS works well with real biological samples.     

Crack identification by ‘arrival time’ using XFEM and a genetic algorithm

A computational framework is developed in which cracks in two‐dimensional structures are identified, in conjunction with non‐destructive testing of specimens. As opposed to a previous study by the authors, which was based on time‐harmonic excitation with a single frequency, here the transient response of the structure to a short‐duration signal is measured along part of the external boundary. Crack detection is performed using the solution of an inverse time‐dependent problem. It is shown that the arrival time of the input signal to the points of measurement is a good criterion for crack identification in the time domain. The inverse problem of identification is solved using a genetic algorithm, while each forward problem is solved by the time‐dependent extended finite element method (XFEM). The XFEM scheme is efficient in that it allows the use of a single regular mesh for a large number of forward time response problems with different crack geometries. Numerical examples involving a crack in a flat membrane are presented. Identification based on ‘arrival time’ is shown to perform better than that based on time‐harmonic response. Copyright © 2008 John Wiley & Sons, Ltd.