Orientadores: Milton Dias Junior e Vicente Lopes Junior / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-10T04:58:56Z (GMT). No. of bitstreams: 1 Silva_Samuelda_D.pdf: 9025537 bytes, checksum: ac86884d08ba00adbf77aeac335e7acc (MD5) Previous issue date: 2008 / Resumo: A contribuição deste trabalho foi desenvolver uma metodologia para detecção e localização de danos considerando apenas respostas de deslocamento ou aceleração e medidas obtidas por atuadores e sensores piezelétricos (PZTs) distribuídos e colados em estruturas flexíveis. Modelos de filtros discretos do tipo auto-regressivos, como AR-ARX, ARMA e ARMAX, são usados para extrair um indicador de danos a partir dos erros de predição linear destes filtros. Investiga-se também o uso de séries discretas de Wiener/Volterra escritas com filtros de Kautz para obtenção de erros de predição não-lineares. Para classificar os erros de predição (lineares ou não-lineares) nas classes ¿sem dano¿ ou ¿com dano¿ comparou-se o uso de ferramentas não-supervisionadas de classificação de padrões estatísticos, como agrupamento fuzzy e controle estatístico de processos. Testes numéricos e experimentais foram realizados e os resultados alcançados com a metodologia desenvolvida apresentaram vantagens em relação aos métodos convencionais que são discutidas no decorrer do trabalho / Abstract: This work proposes a novel approach to detect and locate incipient damage in structures by using only acceleration responses and coupled piezoelectric actuators and sensors. Though the major focus in smart damage detection is given by on the monitoring of the electrical impedance in the frequency domain, the current contribution applies a novel technique based on time series analysis. Regressive models, such as AR-ARX, ARMA and ARMAX, are employed to extract a feature index using the linear prediction errors. The use of nonlinear prediction by using discrete-time Wiener/Volterra models expanded by Kautz filter is also investigated. In order to decide correctly whether damage exists or not, a set of unsurpervised statistical pattern recognition techniques, namely the fuzzy clustering and the statistical process control, are implemented. Several numerical and experimental tests are performed to illustrate and compare the methodology developed with classical approaches. The efficacy of the approach is demonstrated through these tests / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica

A utilização de materiais piezoelétricos, na função de sensores e atuadores distribuídos, para o controle e monitoramento de vibrações estruturais tem um enorme potencial de aplicação nas indústrias aeronáutica, aeroespacial, automobilística e eletroeletrônica. O uso de sensores piezoelétricos integrados para monitoramento de integridade estrutural (ou detecção de falhas), em particular, tem evoluído bastante na última década. Por conseguinte, o número de técnicas utilizadas para esse fim são as mais variadas possíveis. Dentre elas estão às técnicas que avaliam o efeito dos danos em baixa freqüência usando parâmetros modais, em especial freqüências naturais e modos, ou em média-alta freqüência medindo-se a impedância/admitância eletromecânica. O objetivo dessa dissertação é desenvolver, com auxílio de um modelo 2D ANSYS em elementos finitos, uma análise de diferentes técnicas para detecção da posição e tamanho da delaminação em estruturas compósitas utilizando pastilhas piezoelétricas. Várias métricas e técnicas são avaliadas em termos de sua capacidade de identificar, com relativa acurácia, a presença, localização e severidade do dano. Os resultados mostram que ambas as técnicas modal e baseada na impedância são capazes de identificar a presença de danos do tipo delaminação, desde que as pastilhas piezoelétricas estejam próximas do dano. Também é mostrado que as técnicas baseadas na impedância parecem ser mais eficientes do que as modais para detecção da posição e tamanho da delaminação. / The use of piezoelectric materials in the function of distributed sensors and actuators for the control and monitoring of structural vibrations has enormous potential for application in the aeronautical, aerospace, automotive and electronics. The use of integrated piezoelectric sensors for structural health monitoring (or damage detection), in particular, has evolved greatly over the last decade. Consequently, the numbers of techniques used for this purpose are highly diverse. Among them are techniques that evaluate the effect of damages on low frequency modal parameters, especially natural frequencies and mode shapes, or on medium-high frequency measurements of electromechanical impedance/admittance. The objective of this dissertation is to perform, with the aid of a 2D ANSYS finite element model, an analysis of different techniques for the detection of position and size of a delamination in a composite structure using piezoelectric patches. Several metrics and techniques are evaluated in terms of their capability of identifying, with relative accuracy, the presence, location and severity of the damage. Results show that both modal and impedance-based techniques are able to identify the presence of the delamination-type damages, provided the piezoelectric patches are close enough to the damage. It is also shown that impedance-based techniques seem more effective than modal ones for the detection of delamination position and size.

The use of information and communications technology (ICT) to provide medical information, interaction between patients and health-service providers, institution-to-institution transmission of data, in known as eHealth. ICT have become an inseparable part of our life, it can integrate health care more seamlessly to our everyday life. ICT enables the delivery of accurate medical information anytime anywhere in an efficient manner. Cardiovascular disease (CVD) is the single leading cause of death, especially in elderly people. The condition of heart is monitor by electrocardiogram (ECG). The Electrocardiogram (ECG) is widely used clinical tool to diagnose complex heart diseases. In clinical settings, resting ECG is used to monitor patients. Holter-based portable monitoring solutions capable of 24 to 48-hour ECG recording, they lack the capability of providing any real-time feedback in case of alarming situation. The recorded ECG data analyzed offline by doctor. To address this issue, authors propose a functionality of intelligence decision support system, in heart monitoring system. The proposed system has capability of generate an alarm in case of serious abnormality in heart, during monitoring of heart activity.

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

Composites are in high demand; however, fasteners are often required for joining process and can reduce their advantages. One solution is adhesive bonding, but uncertainty exists regarding long term durability and the ability to interrogate bonds noninvasively. One potential solution to qualify bond integrity over its service life is to dope an adhesive with magneto-electric nanoparticles (MENs). MENs can yield output magnetic signatures that are influenced by bond quality and damage state. In this study, adhesives have been doped with MENs prior to bonding at 1% volume concentration. For optimum implementation, this health monitoring system should be evaluated for effects of the MENs on the mechanical properties. Lap-shear testing was conducted to assess changes in the bond strength from addition of the nanoparticles. End-notched flexure (ENF) tests were also conducted for fracture mechanism evaluation. Results showed an increase of 12% in shear strength as a function of MENs loading concentration. In addition, a feasibility study of output magnetic signature as a function of elevated temperature and humidity were evaluated for MENs doped and un-doped adhesives. Results gave an order of magnitude change in magnetic signal as a function of exposure time.

The problem of vibration induced structural faults has been a real one in engineering over the years. If left unchecked it has led to the unexpected failures of so many structures. Needless to say, this has caused both economic and human life losses. Therefore for over forty years, structural damage identification has been one of the important research areas for engineers. There has been a thrust to develop global structural damage identification techniques to complement and/or supplement the long-practised local experimental techniques. In that respect, studies have shown that vibration-based techniques prove to be more potent. Most of the existing vibration-based techniques monitor changes in modal properties like natural frequencies, damping factors and mode shapes of the structural system to infer the presence of structural damage. Literature also reports other techniques which monitor changes in other vibration quantities like the frequency response functions, transmissibility functions and time-domain responses. However, none of these techniques provide a complete identification of structural damage. This study presents a damage detection technique based on operational response monitoring, which can identify all the four levels of structural damage and be implemented as a continuous structural health monitoring technique. The technique is based on monitoring changes in internal data variability measured by a test statistic <font face="symbol">c</font>2Ovalue. Structural normality is assumed when the <font face="symbol">c</font>2Om value calculated from a fresh set of measured data is within the limits prescribed by a threshold <font face="symbol">c</font>2OTH value . On the other hand, abnormality is assumed when this threshold value has been exceeded. The quantity of damage is determined by matching the <font face="symbol">c</font>2Om value with the <font face="symbol">c</font>2Op values predicted using a benchmark finite element model. The use of <font face="symbol">c</font>2O values is noted to provide better sensitivity to structural damage than the natural frequency shift technique. The analysis carried out on a numerical study showed that the sensitivity of the proposed technique ranged from three to thousand times as much as the sensitivity of the natural frequencies. The results from a laboratory structure showed that accurate estimates of damage quantity and remaining service life could be achieved for crack lengths of less than 0.55 the structural thickness. This was due to the fact that linear elastic fracture mechanics theory was applicable up to this value. Therefore, the study achieved its main objective of identifying all four levels of structural damage using operational response changes. / Dissertation (MSc (Mechanics))--University of Pretoria, 2007. / Mechanical and Aeronautical Engineering / unrestricted

The development of internet-based technologies, the design and adoption of wireless wearable and smart devices have been a growing study spot in all domains. The healthcare sector as many others is making technological progress to improve healthcare services and patients wellbeing and avoid or minimize the use of manual and traditional practices such as the use of paper notes to record the vital signs parameters data. The vital signs parameters are the most monitored physiology features, they produce a big amount of data and request a close follow up to define the health condition of a patient. Continuous vital signs monitoring involves the usage of different devices and systems, which if appropriate positively impact the activities involved, by enabling the continuous generation of data and information about the overall health status of patients and contribute to the wellbeing of individuals, in terms of preventing and reducing fatal risks. To investigate this situation, this research’s focus was in three parts; first, investigate recent research about patient’s health predictions based on vital signs parameters and the impacts of continuous monitoring on the care given. Second, explore the availability in terms of i.e. sensors used in devices that can continuously track vital signs parameters. Last, to provide a possible design recommendation to improve and/or replace the existing devices for vital signs parameters measuring and monitoring in emergency and post-operative care. A qualitative approach and participatory design approach were used to collect data. The qualitative part was achieved through interviews and the participatory design part was accomplished by the future workshop and two prototyping techniques, paper and digital prototypes. The findings of this research were analysed using conceptual analysis, and also discussed using those concepts. Together with the participants, this research resulted in three design suggestions which if implemented shall improve the vital signs continuous monitoring activities, by facilitating the healthcare professionals in their clinical responsibilities and improving the patients wellbeing while admitted in Emergency and Post-operative wards.

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<p>Developing a reliable in-situ non-destructive testing method to determine the strength of in-place concrete is critical because a fast-paced construction schedule exposes concrete pavement and/or structures undergoing substantial loading conditions, even at their early ages. Conventional destructive testing methods, such as compressive and flexural tests, are very time-consuming, which may cause construction delays or cost overruns. Moreover, the curing conditions of the tested cylindrical samples and the in-place concrete pavement/structures are quite different, which may result in different strength values. An NDT method that could directly correlate the mechanical properties of cementitious materials with the sensing results, regardless of the curing conditions, mix design, and size effect is needed for the in-situ application.</p><p>The piezoelectric sensor-based electromechanical impedance (EMI) technique has shown promise in addressing this challenge as it has been used to both monitor properties and detect damages on the concrete structure. Due to the direct and inverse effects of piezoelectric, this material can act as a sensor, actuator, and transducer. This research serves as a comprehensive study to investigate the feasibility and efficiency of using piezoelectric sensor-based EMI to evaluate the strength of newly poured concrete. To understand the fundamentals of this method and enhance the durability of the sensor for in-situ monitoring, this work started with sensor fabrication. It has studied two types of polymer coating on the effect of the durability of the sensor to make it practical to be used in the field.</p><p>The mortar and concrete samples with various mix designs were prepared to ascertain whether the results of the proposed sensing technique were affected by the different mixtures. The EMI measurement and compressive strength testing methods (ASTM C39, ASTM C109) were conducted in the laboratory. The experimental results of mortar samples with different water-to-cement ratios (W/C) and two types of cement (I and III) showed that the correlation coefficient (R²) is higher than 0.93 for all mixes. In the concrete experiments, the correlation coefficient between the EMI sensing index and compressive strength of all mixes is higher than 0.90. The empirical estimation function was established through a concrete slab experiment. Moreover, several trial implementations on highway construction projects (I-70, I-74, and I-465) were conducted to monitor the real-time strength development of concrete. The data processing method and the reliable index of EMI sensing were developed to establish the regression model to correlate the sensing results with the compressive strength of concrete. It has been found that the EMI sensing method and its related statistical index can effectively reflect the compressive strength gain of in-place concrete at different ages.</p><p>To further investigate the in-situ compressive strength of concrete for large-scale structures, we conducted a series of large concrete slabs with the dimension of 8 feet × 12 feet × 8 inches in depth was conducted at outdoor experiments field to simulate real-world conditions. Different types of compressive strength samples, including cast-in-place (CIP) cylinder (4” × 6”) – (ASTM C873), field molded cylinder (4” × 8”) – (ASTM C39), and core drilled sample (4” × 8”) – (ASTM C42) were prepared to compare the compressive strength of concrete. The environmental conditions, such as ambient temperatures and relative humidity, were also recorded. The in-situ EMI monitoring of concrete strength was also conducted. The testing ages in this study were started from 6 hours after the concrete cast was put in place to investigate the early age results and continued up to 365 days (one year) later for long-term monitoring. The results indicate that the strength of the CIP sample is higher than the 4” x 8” molded cylinder , and that core drilled concrete is weaker than the two aforementioned. The EMI results obtained from the slab are close to those obtained from CIP due to similar curing conditions. The EMI results collected from 4 × 8-inch cylinder samples are lower than slab and CIP, which aligns with the mechanical testing results and indicates that EMI could capture the strength gain of concrete over time.</p><p>The consequent database collected from the large slab tests was used to build a prediction model for concrete strength. The Artificial Neuron Network (ANN) was investigated and experimented with to optimize the prediction of performances. Then, a sensitivity analysis was conducted to discuss and understand the critical parameters to predict the mechanical properties of concrete using the ML model. A framework using Generative Adversarial Network (GAN) based on algorithms was then proposed to overcome real data usage restrictions. Two types of GAN algorithms were selected for the data synthesis in the research: Tabular Generative Adversarial Networks (TGAN) and Conditional Tabular Generative Adversarial Networks (CTGAN). The testing results suggested that the CTGAN-NN model shows improved testing performances and higher computational efficiency than the TGAN model. In conclusion, the AI-guided concrete strength sensing and prediction approaches developed in this dissertation will be a steppingstone towards accomplishing the reliable and intelligent assessment of in-situ concrete structures.</p><br>