Navegando por Assunto "Structural health monitoring"

Agora exibindo 1 - 6 de 6

Acesso aberto (Open Access)
Desenvolvimento de sensores baseados em fibra óptica para monitoramento estrutural
(Universidade Federal do Pará, 2016-04-01) FERNANDES, Cindy Stella; GIRALDI, Maria Thereza Miranda Rocco; http://lattes.cnpq.br/0270661833822671; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
The research and development of systems for measuring physical and mechanical parameters of structural health, allows the early detection of collapses, deterioration process and other natural and / or caused by man factors. In this case, real-time measurements of these parameters are crucial for identification, localization and quantification of damages, and also improve the maintenance and safety of such structures. Curvature and vibration measurements are important to structural monitoring due to their relationship with the dynamic responses of engineering structures. In this thesis, core diameter mismatch structures are proposed and experimentally investigated for curvature and vibration sensing. Among the analyzes, two settings exhibited improved performance, one approach uses a structure formed by splicing an uncoated short section of multimode fiber between two standard single mode fibers (SMS), combined to an optical fiber mirror at its end, and the other approach is made by the sandwich of one single mode fiber section between two short multimode fiber sections, spliced between two standard single mode fibers (SMSMS). The SMS device is analyzed through experimental measurements and numerical simulations. In the curvature analysis, the proposed SMS sensor generates destructive interference patterns whether it is bent, varying only the attenuation of the optical signal without wavelength shifts. Numerical modeling is performed using the finite difference beam propagation method by means of the BeamProp 9.0 software of Rsoft™ company. In the experimental vibration analysis, the SMSMS sensor is formed by two MMF sections that act as coupler and re-coupler of core-cladding modes, and the SMF section in the middle acts as the "arm" of interference. So the cladding modes that propagate in the SMF middle section become sensitive to the applied frequencies. The SMSMS vibration sensor proved to be suitable to monitor very low frequencies such as 0.1 Hz. The proposed sensors configurations present several interesting features, such as easy fabrication, low-cost, high-efficiency, and high sensitivity. Although the manufacturing process of the structures is not very precise, which affects its reproducibility, such sensors very useful in a wide range of applications, such as structural health monitoring.
Acesso aberto (Open Access)
Desenvolvimento e implementação de um sistema de monitoramento de integridade estrutural baseado em rede de sensores
(Universidade Federal do Pará, 2016-08-12) NUNES, Flávio Hernan Figueiredo; KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha; http://lattes.cnpq.br/1596629769697284
The objective of this dissertation is show the design of a structural integrity monitoring system, employing sensor network. The project of sensor node allows many kind of sensors, such as electrical strain gage, accelerometer, temperature sensor, humidit sensor, also the sensor node is capable of communicating via wireless and wired technology. In contrast to conventional systems that are centralized and employ long cables, the use of a sensor network is a decentralized approach, allowing the sensors are closer to the conditioning circuit, this brings certain bene_ts, such as reducing the length of the sensor cables decreasing the uptake of electromagnetic noise and decrease the impedance of the cable, improving the response signals generated by sensors. They will be presented details of the circuit and the sensor node communication.
Acesso aberto (Open Access)
Machine learning algorithms for damage detection in structures under changing normal conditions
(Universidade Federal do Pará, 2017-01-31) SILVA, Moisés Felipe Mello da; SALES JÚNIOR, Claudomiro de Souza de; http://lattes.cnpq.br/4742268936279649; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
Engineering structures have played an important role into societies across the years. A suitable management of such structures requires automated structural health monitoring (SHM) approaches to derive the actual condition of the system. Unfortunately, normal variations in structure dynamics, caused by operational and environmental conditions, can mask the existence of damage. In SHM, data normalization is referred as the process of filtering normal effects to provide a proper evaluation of structural health condition. In this context, the approaches based on principal component analysis and clustering have been successfully employed to model the normal condition, even when severe effects of varying factors impose difficulties to the damage detection. However, these traditional approaches imposes serious limitations to deployment in real-world monitoring campaigns, mainly due to the constraints related to data distribution and model parameters, as well as data normalization problems. This work aims to apply deep neural networks and propose a novel agglomerative cluster-based approach for data normalization and damage detection in an effort to overcome the limitations imposed by traditional methods. Regarding deep networks, the employment of new training algorithms provide models with high generalization capabilities, able to learn, at same time, linear and nonlinear influences. On the other hand, the novel cluster-based approach does not require any input parameter, as well as none data distribution assumptions are made, allowing its enforcement on a wide range of applications. The superiority of the proposed approaches over state-of-the-art ones is attested on standard data sets from monitoring systems installed on two bridges: the Z-24 Bridge and the Tamar Bridge. Both techniques revealed to have better data normalization and classification performance than the alternative ones in terms of false-positive and false-negative indications of damage, suggesting their applicability for real-world structural health monitoring scenarios.
Acesso aberto (Open Access)
Output-only methods for damage identification in structural health monitoring
(Universidade Federal do Pará, 2017-04-27) SANTOS, Adam Dreyton Ferreira dos; FIGUEIREDO, Elói João Faria; http://lattes.cnpq.br/2315380423001185; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
In the structural health monitoring (SHM) field, vibration-based damage identification has become a crucial research area due to its potential to be applied in real-world engineering structures. Assuming that the vibration signals can be measured by employing different types of monitoring systems, when one applies appropriate data treatment, damage-sensitive features can be extracted and used to assess early and progressive structural damage. However, real-world structures are subjected to regular changes in operational and environmental conditions (e.g., temperature, relative humidity, traffic loading and so on) which impose difficulties to identify structural damage as these changes influence different features in a distinguish manner. In this thesis by papers, to overcome this drawback, novel output-only methods are proposed for detecting and quantifying damage on structures under unmeasured operational and environmental influences. The methods are based on the machine learning and artificial intelligence fields and can be classified as kernel- and cluster-based techniques. When the novel methods are compared to the state-of-the-art ones, the results demonstrated that the former ones have better damage detection performance in terms of false-positive (ranging between 3.65.4%) and false-negative (ranging between 0-2.6%) indications of damage, suggesting their applicability for real-world SHM solutions. If the proposed methods are compared to each other, the cluster-based ones, namely the global expectation-maximization approaches based on memetic algorithms, proved to be the best techniques to learn the normal structural condition, without loss of information or sensitivity to the initial parameters, and to detect damage (total errors equal to 4.4%).
Acesso aberto (Open Access)
Projeto e implementação de um nodo sensor para aquisição de sinais de extensômetros em redes de sensores sem fio aplicado ao monitoramento de deformações em estruturas
(Universidade Federal do Pará, 2012-07-09) ATAÍDE, Rodrigo Williams Rodrigues; KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha; http://lattes.cnpq.br/1596629769697284
This dissertation’s main objective is to propose a node wireless sensor for use in wireless sensor networks, in data strain gage acquisition systems. The acquisition system for the strain is based on the Wheatstone bridge and enables various settings. The processing and wireless communication is performed by ATmega128RFA1, composed of a microcontroller and a radio-frequency transceiver with the Zigbee standard. The node is designed to ensure reliability in data acquisition and be fully controlled remotely. Among the controllable parameters are: the signal gain and sampling rate. In addition, the node has resources to make the balance of the Wheatstone bridge automatically. The choice of components, based on criteria related to energy consumption and cost the same. It was designed a printed circuit board (PCB) for the node, and regarding it, estimates of energy consumption and value of the prototype were made, with the aim of analyzing its viability. Besides the design of the sensor node, the dissertation presents the proposal of its integration in a wireless sensor network (WSN), including the suggestion of complementary hardware and software developments. For testing, a node sensor was constructed experimentally and used a force transducer.
Acesso aberto (Open Access)
Proposta de gerenciamento de dados para monitoramento de saúde estrutural utilizando redes de sensores ópticos FBG
(Universidade Federal do Pará, 2014-06-09) SANTOS, Adam Dreyton Ferreira dos; SALES JUNIOR, Claudomiro de Souza de; http://lattes.cnpq.br/4742268936279649; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
Due to their unique characteristics, optical sensor networks have found application in many fields, such as in Civil and Geotechnical Engineering, Aeronautics, Energy and Oil & Gas Industries. Monitoring solutions based on this technology have proven particularly cost effective and can be applied to large scale structures where hundreds of sensors must be deployed for long term measurement of different mechanical and physical parameters. Sensors based on Fiber Bragg gratings (FBGs) are the most common solution used in Structural Health Monitoring (SHM) and the measurements are performed by special instruments known as optical interrogators. Acquisition rates increasingly higher have been possible using the latest optical interrogators, which gives rise to a large volume of data whose manipulation, storage, management and visualization can demand special software applications. This work presents two real-time software applications developed for these purposes: Interrogator Abstraction (InterAB) and Web-based System (WbS). The innovations in this work include the integration, synchronization, independence, security, processing and real-time visualization, and data persistence or storage provided by joint work of developed applications. The results obtained during tests in laboratory and real environment demonstrate the efficiency, robustness and flexibility of these softwares for different types of sensors and optical interrogators, ensuring atomicity, consistency, isolation and durability of data persisted by InterAB and displayed by WbS.