Finite Element Modeling of Spiral Frequency Steerable Acoustic Transducers (FSATs) for guided waves based Structural Health Monitoring of plate-like structures

Structural Health Monitoring (SHM) is an emerging area of research associated to improvement of maintainability and the safety of aerospace, civil and mechanical infrastructures by means of monitoring and damage detection. Guided wave structural testing method is an approach for health monitoring of plate-like structures using smart material piezoelectric transducers. Among many kinds of transducers, the ones that have beam steering feature can perform more accurate surface interrogation. A frequency steerable acoustic transducer (FSATs) is capable of beam steering by varying the input frequency and consequently can detect and localize damage in structures. Guided wave inspection is typically performed through phased arrays which feature a large number of piezoelectric transducers, complexity and limitations. To overcome the weight penalty, the complex circuity and maintenance concern associated with wiring a large number of transducers, new FSATs are proposed that present inherent directional capabilities when generating and sensing elastic waves. The first generation of Spiral FSAT has two main limitations. First, waves are excited or sensed in one direction and in the opposite one (180 ̊ ambiguity) and second, just a relatively rude approximation of the desired directivity has been attained. Second generation of Spiral FSAT is proposed to overcome the first generation limitations. The importance of simulation tools becomes higher when a new idea is proposed and starts to be developed. The shaped transducer concept, especially the second generation of spiral FSAT is a novel idea in guided waves based of Structural Health Monitoring systems, hence finding a simulation tool is a necessity to develop various design aspects of this innovative transducer. In this work, the numerical simulation of the 1st and 2nd generations of Spiral FSAT has been conducted to prove the directional capability of excited guided waves through a plate-like structure.

Structural Data Acquisition Using Sensor Network

The development cost of any civil infrastructure is very high; during its life span, the civil structure undergoes a lot of physical loads and environmental effects which damage the structure. Failing to identify this damage at an early stage may result in severe property loss and may become a potential threat to people and the environment. Thus, there is a need to develop effective damage detection techniques to ensure the safety and integrity of the structure. One of the Structural Health Monitoring methods to evaluate a structure is by using statistical analysis. In this study, a civil structure measuring 8 feet in length, 3 feet in diameter, embedded with thermocouple sensors at 4 different levels is analyzed under controlled and variable conditions. With the help of statistical analysis, possible damage to the structure was analyzed. The analysis could detect the structural defects at various levels of the structure.

Directly training spiking neural networks for cyber-physical systems: from supervised to reinforcement learning

Spiking Neural Networks (SNNs) are bio-inspired Artificial Neural Networks (ANNs) utilizing discrete spiking signals, akin to neuron communication in the brain, making them ideal for real-time and energy-efficient Cyber-Physical Systems (CPSs). This thesis explores their potential in Structural Health Monitoring (SHM), leveraging low-cost MEMS accelerometers for early damage detection in motorway bridges. The study focuses on Long Short-Term SNNs (LSNNs), although their complex learning processes pose challenges. Comparing LSNNs with other ANN models and training algorithms for SHM, findings indicate LSNNs' effectiveness in damage identification, comparable to ANNs trained using traditional methods. Additionally, an optimized embedded LSNN implementation demonstrates a 54% reduction in execution time, but with longer pre-processing due to spike-based encoding. Furthermore, SNNs are applied in UAV obstacle avoidance, trained directly using a Reinforcement Learning (RL) algorithm with event-based input from a Dynamic Vision Sensor (DVS). Performance evaluation against Convolutional Neural Networks (CNNs) highlights SNNs' superior energy efficiency, showing a 6x decrease in energy consumption. The study also investigates embedded SNN implementations' latency and throughput in real-world deployments, emphasizing their potential for energy-efficient monitoring systems. This research contributes to advancing SHM and UAV obstacle avoidance through SNNs' efficient information processing and decision-making capabilities within CPS domains.

Single side damage simulations and detection in beam-like structures

Beam-like structures are the most common components in real engineering, while single side damage is often encountered. In this study, a numerical analysis of single side damage in a free-free beam is analysed with three different finite element models; namely solid, shell and beam models for demonstrating their performance in simulating real structures. Similar to experiment, damage is introduced into one side of the beam, and natural frequencies are extracted from the simulations and compared with experimental and analytical results. Mode shapes are also analysed with modal assurance criterion. The results from simulations reveal a good performance of the three models in extracting natural frequencies, and solid model performs better than shell while shell model performs better than beam model under intact state. For damaged states, the natural frequencies captured from solid model show more sensitivity to damage severity than shell model and shell model performs similar to the beam model in distinguishing damage. The main contribution of this paper is to perform a comparison between three finite element models and experimental data as well as analytical solutions. The finite element results show a relatively well performance.

Detection of beetle damage in forests by X-ray CT image processing

Some beetle species can have devastating economic impacts on forest and nursery industries. A recent example is Anophophora glabripennis, a species of beetle known in the United States as the ''Asian Longhorrned beetle'', which has damaged many American forests, and is a threat which can unintentionally reach south American countries, including Brazil. This work presents a new method based on X-ray computerized tomography (CT) and image processing for beetle injury detection in forests. Its results show a set of images with correct identification of the location of beetles in living trees as well as damage evaluation with time.

Chromosome damage in underground coal miners: detection by conventional cytogenetic techniques and by submitting lymphocytes of unexposed individuals to plasma from at-risk groups

Chromosome abnormalities and the mitotic index in lymphocyte cultures and micronuclei in buccal mucosa cells were investigated in a sample of underground mineral coal miners from Southern Brazil. A decreased mitotic index, an excess of micronuclei and a higher frequency of chromosome abnormalities (fragments, polyploidy and overall chromosome alterations) were observed in the miners when compared to age-paired normal controls from the same area. An alternative assay for clastogenesis in occupational exposition was tested by submitting lymphocytes from non-exposed individuals to a pool of plasmas from the exposed population. This assay proved to be very convenient, as the lymphocytes obtained from the same individuals can be used as target as well as control cells. Also, it yielded a larger number of metaphases and of successful cultures than with common lymphocyte cultures from miners. A significantly higher frequency of chromatid gaps, fragments and overall alterations were observed when lymphocytes from control subjects were exposed to miner plasma pools. Control plasma pools did not significantly induce any type of chromosome alterations in the cultures of normal subjects, thus indicating that the results are not due to the effect of the addition of plasma pools per se.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Immunochemical detection of UV-induced DNA damage and repair

The application of an antiserum to ultraviolet radiation (UVR)-damaged DNA is presented. A novel experimental system was employed to ascertain the limits of detection for this antiserum. Using a DNA standard containing a known amount of dimer, the limits of detection were found to be 0.9 fmol of dimer. This was compared to a limit of 20-50 fmol dimer using gas chromatography-mass spectrometry (GC-MS). Induction of thymine dimers in DNA following UVR exposure, as assessed using this antiserum in an enzyme-linked immunosorbent assay (ELISA), was compared with GC-MS measurements. The ELISA method successfully demonstrated the induction of lesions in DNA irradiated either with UVC or UVB, although despite high sensitivity, no discernible binding was seen to UVA-irradiated DNA. The antiserum was also shown to be applicable to immunocytochemistry, localising damage in the nuclei of UVR exposed keratinocytes in culture. The ability of the antiserum to detect DNA damage in skin biopsies of individuals exposed to sub-erythemal doses of UVR was also demonstrated. Moreover, the subsequent removal of this damage, as evidenced by a reduction in antiserum staining, was noted in sections of biopsies taken in the hours following irradiation. © 2003 Elsevier B.V. All rights reserved.

Immunochemical detection of glyoxal DNA damage

The relevance of reactive oxygen species (ROS) in the pathogenesis of inflammatory diseases is widely documented. Immunochemical detection of ROS DNA adducts has been developed, however, recognition of glyoxal-DNA adducts has not previously been described. We have generated a polyclonal antibody that has shown increased antibody binding to ROS-modified DNA in comparison to native DNA. In addition, dose-dependent antibody binding to DNA modified with ascorbate alone was shown, with significant inhibition by desferrioxamine, catalase, and ethanol. Minimal inhibition was observed with uric acid, 1,10-phenanthroline and DMSO. However, antibody binding in the presence of EDTA increased 3500-fold. The involvement of hydrogen peroxide and hydroxyl radical in ascorbate-mediated DNA damage is consistent with ascorbate acting as a reducing agent for DNA-bound metal ions. Glyoxal is known to be formed during oxidation of ascorbate. Glyoxylated DNA, that previously had been proposed as a marker of oxidative damage, was recognised in a dose dependent manner using the antibody. We describe the potential use of our anti-ROS DNA antibody, that detects predominantly Fenton-type mediated damage to DNA and report on its specificity for the recognition of glyoxal-DNA adducts.

Online trendy topics detection in microblogs with selective user monitoring under cost constraints

As microblog services such as Twitter become a fast and convenient communication approach, identification of trendy topics in microblog services has great academic and business value. However detecting trendy topics is very challenging due to huge number of users and short-text posts in microblog diffusion networks. In this paper we introduce a trendy topics detection system under computation and communication resource constraints. In stark contrast to retrieving and processing the whole microblog contents, we develop an idea of selecting a small set of microblog users and processing their posts to achieve an overall acceptable trendy topic coverage, without exceeding resource budget for detection. We formulate the selection operation of these subset users as mixed-integer optimization problems, and develop heuristic algorithms to compute their approximate solutions. The proposed system is evaluated with real-time test data retrieved from Sina Weibo, the dominant microblog service provider in China. It's shown that by monitoring 500 out of 1.6 million microblog users and tracking their microposts (about 15,000 daily) with our system, nearly 65% trendy topics can be detected, while on average 5 hours earlier before they appear in Sina Weibo official trends.

Cost-effective node monitoring for online hot event detection in sina weibo microblogging

We propose a cost-effective hot event detection system over Sina Weibo platform, currently the dominant microblogging service provider in China. The problem of finding a proper subset of microbloggers under resource constraints is formulated as a mixed-integer problem for which heuristic algorithms are developed to compute approximate solution. Preliminary results show that by tracking about 500 out of 1.6 million candidate microbloggers and processing 15,000 microposts daily, 62% of the hot events can be detected five hours on average earlier than they are published by Weibo.

Detection of seismic damage in buildings using time series analysis and pattern recognition

Peer reviewed

Detection of anti-Toxoplasma gondii antibodies in experimentally and naturally infected non-human primates by Indirect Fluorescence Assay (IFA) and indirect ELISA

The Indirect Fluorescence Assay (IFA) and the indirect ELISA were comparatively used to detect IgG and IgM antibodies for Toxoplasma gondii in experimentally and naturally infected primates. In the experimentally infected group, antibodies of diagnostic value were detected at day 9 post-infection (PI) with the IFA (IgG and IgM) and with IgG-ELISA. IgM-ELISA detected antibodies for T. gondii starting at day 3 PI until the end of the experiment (102 days PI). Of the 209 naturally infected sera tested, from many zoos of State of Sao Paulo, 64.59 and 67.94% were positive in the IgG-IFA test and IgG-ELISA respectively. IgM-ELISA test detected seropositivity in 52.63% of the sera although IgM-IFA test detected it in only in 0.96% of the samples. The differential toxoplasmosis diagnosis was accomplished with Neospora caninum by IFA, observing 61 (29.2%) seropositive animals for this parasite and 149 (70.8%) negative. Sixty animals were positive for both T. gondii and N. caninum. Pneumonia, splenomegaly, and intestinal ulcers were macroscopically observed. Unremarkable interstitial pneumonia, enteritis, colitis, splenitis, and glomerulitis were microscopically observed. The immunohistochemical stain could not detect the presence of T. gondii in the tissues of the animals infected experimentally.