Papers by Jose dos Reis Vieira de Moura Junior
Observatorio de la economía latinoamericana, Jun 16, 2023
Steel structures undergo loads and stresses during service life, subject to structural damages su... more Steel structures undergo loads and stresses during service life, subject to structural damages such as fatigue, corrosion, cracks, and plastic deformations. Therefore, to detect damage, the dynamic responses of the structures are used, comparing two states: with and without damage. These dynamic responses are obtained from a signal representing the structure's electromechanical impedance. Thus, these impedance signatures must accurately represent the analyzed structure. By comparing the impedance signatures of the low-cost device used at UFG/UFCAT with the SySHM system developed by LMEst/UFU, it can be observed that the low-cost equipment requires calibration in its impedance measurements. This work proposes a method based on the Least-Squares approach to determine a mathematical model to convert the signals acquired by the lowcost device into signals suitable for analysis. In conclusion, it was feasible to demonstrate the utilization potential of the cost-effective device under impedance-based monitoring conditions.
Observatorio de la economía latinoamericana, May 9, 2023
to determine the existence of damage in an aluminum beam using the Root Square Deviation (RMSD) d... more to determine the existence of damage in an aluminum beam using the Root Square Deviation (RMSD) damage metric. Furthermore, this contribution aims to apply the concept of stochastic evaluation in the context of the electromechanical impedance-based SHM technique by using the Monte Carlo method to generate random numbers. The development of the work is to validate two models, one with the impedance signals and the other stochastically, and thus build the linear regression model for both. In the end, the results are compared to test the representation of the failure identification in the beam.
Journal of Intelligent Material Systems and Structures, Nov 1, 2006
In this work, techniques of impedance-based structural health monitoring are applied to aeronauti... more In this work, techniques of impedance-based structural health monitoring are applied to aeronautical structures using statistical meta-modeling methods. First, a procedure is developed to find the best test conditions through factorial designs. Also, Taguchi robustness techniques are used to reduce noise influence in damage detection processes. Further, based on meta-models, a procedure is developed for damage identification and characterization, as applied to a vertical fin of an unmanned aerial vehicle (UAV). Structural changes are obtained by using localized adding masses at several determined points along the structure. Finally, by using two meta-models, namely a probabilistic neural network model and a surface response model, it is possible to identify as well as to characterize damage in the structure.
Biblioteca Central da Universidade de Brasilia eBooks, 2022
The electromechanical impedance-based approach can perform Structural Health Monitoring (SHM). Th... more The electromechanical impedance-based approach can perform Structural Health Monitoring (SHM). The impedance signature is used to map any structural change and for follow-up purposes. Two major challenges for SHM are normalizing the collected impedance data and determining strategies to assess the level of damage to engineering structures and equipment over time. The objectives of this chapter are to present a data normalization technique and to illustrate a case study by modeling the damage level of an aluminum beam using Fuzzy Rule-Based Systems (FRBSs) that are generated using the Adaptive Neuro-Fuzzy Inference System (ANFIS). The training is carried out for the first aim with the input variables temperature and frequency, and the output data are impedance baseline signatures. The temperature effect can generate changes in the impedance signature, leading to incorrect structural diagnoses. Because of that, it is necessary to compensate for the impact of this variable for later prediction of impedance signatures without damage at temperatures that were not necessarily observed in the data collection. Results were obtained in the validation, in which a part of the data was used for training the FRBSs, and another racy of the predicted signatures since the highest Correlation Coefficient Deviation (CCD) damage index was 0, 003800021. To evaluate the damage level, FRBSs were constructed, with the input variables being two damage indices established by the electromechanical impedance signatures. The FRBSs average hit percentages are 95%. This result can indicate possible inputs for FBRSs to identify the damage levels when these FRBSs output values are unknown. Finally, the methodology proposed is used for the damage detection process in an experiment to detect corrosion-related damage in metallic structures. .
Biblioteca Central da Universidade de Brasilia eBooks, 2022
Engineering has developed new approaches over the last 50 years in all its areas. Among the diffe... more Engineering has developed new approaches over the last 50 years in all its areas. Among the different areas, the design areas became more agile and computer-based, logistics developed new modes and interactions more Just in Time, while materials engineering revolutionized the options of possibilities in all sectors. However, the maintenance area gains special attention due to its objective to present limiting working conditions. While the production areas allow infinite productivity development, creating new processes and techniques, the maintenance area has a limit of improvement focused on the utopian zero defects. Thus, several techniques have been developed in recent decades, mainly with the advancement of computational power and integration. Techniques for assessing structural integrity have also developed, enabling the implementation of more precise techniques in the qualitative capacity of identifying a failure, as well as quantifying its severity and location. This chapter discusses the Structural Integrity Monitoring Method based on Electromechanical Impedance. This is one of the most explored techniques in recent decades by several research groups in Brazil and worldwide, having applications in aeronautics, space, oil and gas, bioengineering, civil construction, among others. In the next sections, some historical aspects of the technique are presented, as well as basic concepts and variables that influence this monitoring. Finally, a case study of the investigation of a failure simulated by machining an aluminum structure monitored in a climatic chamber is presented. As it is a chapter in which it is more concerned with the fundamentals and aspects that influence the use of the methodology, the conclusions of this case study do not cover any type of statistical modeling or based on machine learning as usually seen in scientific articles in the method. In this case, the effects of temperature on the impedance signature are focused, as well as the calculation of some damage metrics.
Biblioteca Central da Universidade de Brasilia eBooks, 2022
This chapter presents some basic concepts about some fundamental Deep Learning techniques current... more This chapter presents some basic concepts about some fundamental Deep Learning techniques currently used in the data processing. Next, the use of these techniques to aid decision-making in Electromechanical Impedance-based Structural Health Monitoring (ISHM) is presented. Initially, using a CNN to classify structural damage in specimens is evaluated, eliminating the need for temperature compensation. Then, an LSTM network prediction model of the evolution of an accelerated corrosive process (HCl acid) in specimens is presented. Finally, a model based on CNN is carried out as a case study of thickness loss in a real fuel storage tank plate.
Archives of Current Research International
During the last two decades, there has been remarkable growth in the processing capacity of compu... more During the last two decades, there has been remarkable growth in the processing capacity of computers and the evolution of digital cameras. As a result, the thermographic technique and thermal analysis became more applied in electromechanical maintenance due to the low measuring device cost. Simultaneously, new methods based on Deep Learning focused on image and video processing have emerged. In this sense, this contribution aims to verify the applicability of using the deep learning technique of convolutional neural networks to classify patterns of thermographic images of a bench grinder. The methodology used was the collection of thermographic pictures of a bench grinder after starting, without, and after applying loads to the discs. This procedure induced a temperature increase in the grinding machine housing since some types of faults in electric motors can be diagnosed due to over-temperature by thermographic inspection. Furthermore, a Python computational code was developed us...
International Journal of Advanced Engineering Research and Science
In this work, three machine learning approaches were evaluated for detecting anomalies in impedan... more In this work, three machine learning approaches were evaluated for detecting anomalies in impedance-based structural health monitoring (ISHM – Impedance-based Structural Health Monitoring) of a specimen in a controlled environment. Supervised, unsupervised, and semi-supervised algorithms were chosen to compare them regarding detecting anomalies in an aluminum beam with failure induced by surface machining on one of the faces. After applying the algorithms, it was found that, of the three types of learning, supervised and semi-supervised were the ones that achieved the best accuracy in detecting anomalies. On the other hand, the unsupervised type model did not obtain good results for the conditions investigated. Thus, this can be an important technique comparison achievement for implementing real anomaly detection ISHM systems.
Biblioteca Central da Universidade de Brasilia eBooks, 2022
This chapter presents the basic concepts for implementing the guided Lamb Wave method for damage ... more This chapter presents the basic concepts for implementing the guided Lamb Wave method for damage monitoring in mechanical structures. This is one of the structural health monitoring techniques that have been employed in recent years using a network of transducers in order to inspect thin structures. Basically, the methodology allows damage monitoring by comparing the reference signals with the test signals. However, the acquisition systems commonly used in this technique have a high added cost and also require a better level of technical knowledge on the part of the analyst. Thus, this contribution aims to present the development of a low-cost and easy instrumentation system for monitoring structural integrity using Lamb Waves, enabling the use of the technique in field studies, as well as in the context of incipient research in schools.
Revista Cereus, 2021
Mapeamento sistêmico da aplicabilidade da análise de confiabilidade em sistemas de monitoramento ... more Mapeamento sistêmico da aplicabilidade da análise de confiabilidade em sistemas de monitoramento estrutural Systemic mapping of applicability of reliability analysis in structural monitoring systems RESUMO O método de monitoramento da integridade estrutural (SHMdo inglês Structural Health Monitoring) tem sido amplamente utilizado em processos de detecção, localização e quantificação de danos em sistemas mecânicos. Essa área de estudo visa, principalmente, analisar a integridade estrutural dos sistemas mecânicos abrangendo não somente o processo de identificação do dano, mas também ações de correção e controle. De forma paralela, a análise de confiabilidade teve um aumento em pesquisas não só em estruturas, mas também nos materiais compósitos para auxiliar nas probabilidades de falha estrutural de acordo com seus modos de falhar. Este trabalho apresenta uma revisão sistemática da literatura quanto ao desenvolvimento e a aplicabilidade da análise de confiabilidade no monitoramento de falhas em componentes estruturais. Para realização do mapeamento sistemático, utilizou-se as bases de dados do Portal de Periódicos da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), SCOPUS e Web Of Science. Ressalta-se que a execução do processo de mapping study possibilitou a otimização do estudo realizado, bem como possibilitou a identificação dos principais GAP's referentes ao assunto abordado. Os resultados demonstraram que existem estudos quanto a aplicação prática dessa ferramenta em estruturas do cotidiano industrial, porém há uma grande carência de estudos voltados a sistemas ativos de monitoramento.
Este estudo propoe maximizar o numero de atendimentos em um Centro de Estudos Aplicados de Psicol... more Este estudo propoe maximizar o numero de atendimentos em um Centro de Estudos Aplicados de Psicologia (CEAPsi) de uma instituicao federal de ensino, a fim de reduzir a fila de espera, em que trezentas pessoas aguardam por atendimento. Para isso, trata-se de um Problema de Programacao de Quadro de Horarios resolvido atraves de um modelo de Programacao Linear Inteira, sendo a solucao otima obtida com o algoritmo do Gurobi Optimizer. O problema foi modelado com o proposito de se alocar os atendimentos de cada psicologo, respeitando o tipo de atendimento feito em cada sala, o tipo de atendimento realizado por cada psicologo e o horario que ele poderia realizar atendimentos. Alem disso, a carga horaria de cada psicologo foi respeitada. Foram feitos testes com algumas instâncias, mostrando que o modelo e capaz de melhorar a situacao atual do CEAPsi.
Comptes Rendus Mecanique, 2021
Some nondestructive techniques of the Structural Health Monitoring (SHM) have improved their anal... more Some nondestructive techniques of the Structural Health Monitoring (SHM) have improved their analysis in the past decades. Among them, the electromechanical impedance-based SHM technique (EMISHM) has been tested in several fields and associated to different statistical methodologies. Considering the nature of the spatial variation of the damage metric data along structures, herein is proposed the use of the indicator kriging method for predicting the existence of a known damage located in the center of an aluminum plate. Maps showing the probability of the damage metric to fall in several value ranges were capable of outlining the areas affected by the damage and predict its location. Comparisons between scenarios with different spacing between PZT patches showed a reduction in the reliability of the model with the increasing of such spacing. Also, for the structure under study, it demonstrates that it is not possible to obtain results by the methodology for distance between sensors...
REVISTA BRASILEIRA DE BIOMETRIA, 2021
Statistical Process Control (SPC) stands out for the use of control charts and for repeatability ... more Statistical Process Control (SPC) stands out for the use of control charts and for repeatability and reproducibility (R&R) techniques. This work aimed at its applications in the aspects of pre-processing of structural monitoring. The experiment was carried out in a completely randomized design (CRD) with two sources of variation: eight aluminum beams with piezoelectric patches and five types of damage (D1 = baseline, D2 = 0.6g, D3 = 1.1g, D4 = 1.6g, D5 = 2.2g). All measurements were gathered at 30oC and with 20 repetitions for each condition case, producing a damage metric. In the R&R study, a low variation of repetition was observed (9.84%), but a high reproducibility (72.39%), representing that the damage metrics were similar for each situation, but a high variation among beams and damages. Based on this evaluation, the control charts helped to verify in which beams and damages these greatest variabilities were found. Concluding, the control charts for mean and individual measures...
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021
International Journal of Advanced Engineering Research and Science, 2020
The electromechanical impedance-based structural health monitoring is a non-traditional vibration... more The electromechanical impedance-based structural health monitoring is a non-traditional vibration technique that compares a pristine signature to a damaged one. However, in order to compare a complete frequency response function to another, it is necessary to create a virtual index called damage metric, which indicates how far the investigated structure states from the initial condition. The most used index is the RMSD (Root Mean Square Deviation) to have a quantitative measurement of the monitored structures but CCD (Correlation Coefficient Deviation) is more robust to temperature changes. Thus, this contribution focuses on thisCCD damage metric for simulated damages (mass addition) of Al beams in a 2x5 factorial design. The first factor considered was the pristine or damage condition. The second factor was the environmental temperature of the specimen, during the signature gathering, for five levels:-10 o C, 0 o C, 10 o C, 20 o C and 30 o C. According to the references, temperature is a very important aspect to be considered because some changes in the signature can be promoted, and for this purpose a temperature chamber was used in the study. Several statistical evaluations were performed and this contribution illustrates the median of the damage metrics are greater than the baseline ones. Also, although the temperature level creates shifts of the damage metrics, this not caused false positives, enabling the technique to differentiate the damage to the pristine conditions.
Engineering Research Express, 2020
The impedance-based structural health monitoring technique uses measured signatures changes to id... more The impedance-based structural health monitoring technique uses measured signatures changes to identify incipient damages in structures. The purpose is to perform a correlation of these changes with the physical phenomena. However, since electromechanical coupling exists, some environmental influences such as temperature changes may lead to false decision regarding the condition of the structure. As a result, innovative machine learning tools have been extensively investigated to avoid errors in structural prognosis and, in this sense, recent applications of convolutional neural networks (CNN) have emerged within the scope of SHM research, focusing mainly on vibration analysis. However, studies that aim to combine neural architectures with intelligent materials for structural monitoring purposes have been poorly evaluated. Consequently, its integration with the electromechanical impedance method is still considered as being a new application of CNN. Thus, in order to contribute to t...
Proceedings of the 25th International Congress of Mechanical Engineering, 2019
Proceedings of the 25th International Congress of Mechanical Engineering, 2019
Proceedings of the 25th International Congress of Mechanical Engineering, 2019
International Journal of Advanced Engineering Research and Science, 2020
Although SHM (Structural Health Monitoring) has been widely used for aeronautical purposes, in th... more Although SHM (Structural Health Monitoring) has been widely used for aeronautical purposes, in the last decades new application scenarios have become applicable, such as the civil and automotive industries. Automotive components are increasing the maximum operational efficiency, aiming to obtain greater performance and safety of its mechanical systems at low production and maintenance costs. In this context, it is necessary to make predictive studies related to the incipient damages or about the useful life of the structures. The brake system represents one of the most important mechanical systems in a passenger vehicle since it deals directly with the preservation of their lives. Thus, in this contribution a regular vehicle brake disc is studied in order to evaluate the sensitivity of the impedance-based SHM application to identify mechanical changes and propose a method to check their integrities. With the purpose to promote structural changes, a virtual damage was created by mass addition with small magnets attached on the surface of the disc in different positions. Further, some experiments were conducted to have several state conditions of the brake discs (pristine and several virtually damaged cases). Then, the unsupervised machine learning technique called K-Means Clustering Method was applied to the data set and a quadratic regression model was used as well based on RMSD damage metric of the cases. Obtained results show the applicability of the method in the identification of damages, as well as the potential of the use of unsupervised machine learning methods and mathematical models in the context of SHM.
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Papers by Jose dos Reis Vieira de Moura Junior