DSpace Collection:https://repositorio.ufu.br/handle/123456789/192232026-07-21T17:08:23Z2026-07-21T17:08:23ZDetecção de Folga em Cunhas de Geradores Hidrelétricos via Monitoramento de Parâmetros Vibratórioshttps://repositorio.ufu.br/handle/123456789/489132026-07-21T06:27:24Z2026-01-29T00:00:00ZTitle: Detecção de Folga em Cunhas de Geradores Hidrelétricos via Monitoramento de Parâmetros Vibratórios
Abstract: The integrity and efficiency of hydroelectric generators are directly dependent on the stator bar fastening system, composed of wedges and ripple springs. This assembly compensates for thermal expansion and geometric tolerances; however, its loosening constitutes a critical failure. Insufficient clamping allows vibrations under electromagnetic forces, accelerating insulation degradation and intensifying eddy current losses. Consequently, the generator experiences a reduction in its energy conversion capacity. To address this issue, this work proposes a methodology for classifying the tightness level of magnetic wedges through the monitoring of vibratory parameters. The approach integrates experimental and numerical procedures using a simplified system (200 mm wedge and 1 mm top ripple spring). Initially, the dynamic characterization of the assembly was performed on an experimental bench under white noise excitation to identify its natural frequencies. In parallel, a Finite Element Method (FEM) model was developed and calibrated via parametric optimization of mechanical properties. For the wedge, a Young’s modulus (E) of 35 GPa and a Poisson’s ratio (ν) of 0.2 were obtained; for the spring, E = 40 GPa and ν =0.2. With the calibrated model, transient simulations generated 100 acceleration signals for each condition: “loose” (clamping force from 5 to 11 N) and “tight” (11 to 15 N). The final stage involved the training and validation of three classification algorithms using experimental data: k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Autoencoder. The results demonstrated high similarity between synthetic and real signals. The SVM algorithm showed the best performance with 95% accuracy, followed by KNN (92%) and Autoencoder (83%), confirming the potential of the methodology for detecting looseness in wedges.2026-01-29T00:00:00ZDimensionamento e modelagem de um sistema de insuflamento de ar para otimização da queima em uma fornalha de cavacohttps://repositorio.ufu.br/handle/123456789/484522026-03-04T06:26:24Z2026-02-05T00:00:00ZTitle: Dimensionamento e modelagem de um sistema de insuflamento de ar para otimização da queima em uma fornalha de cavaco
Abstract: The use of solid biomass as fuel in industrial thermal systems has become an attractive
alternative from both energy and environmental perspectives. However, the high variability
of the physical and chemical properties of biomass fuels imposes significant challenges to the
combustion process, making the proper design of the air supply and distribution system essential.
In this context, this work aims to perform the design and modeling of an air insufflation system
applied to a eucalyptus wood chip combustion furnace intended to produce 10 tons of steam
per hour, seeking to optimize the combustion process and improve the overall thermal efficiency
of the boiler.
The adopted methodology is initially based on the elemental characterization of the fuel and
on the application of the stoichiometric combustion balance, which allows the determination of
the theoretical and actual air flow rates, considering an appropriate excess air for real operating
conditions. Subsequently, an energy balance of the boiler is carried out to determine the required
fuel mass flow rate, taking into account the lower heating value of the eucalyptus wood chips
and the thermal efficiency of the equipment. Based on these results, the hydraulic design of
the air insufflation system is developed, including the calculation of distributed and localized
pressure losses along ducts and air distribution orifices, as well as the selection of a suitable
fan for the design conditions.
Additionally, a computational fluid dynamics (CFD) analysis is performed to evaluate the
airflow distribution inside the furnace and to identify recirculation zones and the degree of flow
uniformity. The results indicate that the designed system is capable of supplying the required
air flow rate with adequate pressure, providing a more homogeneous oxidant distribution and
contributing to a more efficient and stable combustion process with reduced thermal losses.2026-02-05T00:00:00ZMétodo de melhoria contínua na engenharia de manutenção: estudo de caso em uma indústria alimentícia.https://repositorio.ufu.br/handle/123456789/483572026-02-24T06:20:16Z2025-11-21T00:00:00ZTitle: Método de melhoria contínua na engenharia de manutenção: estudo de caso em uma indústria alimentícia.
Abstract: Industries face the daily challenge of maintaining quality, reducing costs and ensuring the reliability
of their processes. To achieve these goals, many of them adopt management tools focused on
continuous improvement, among which the PDCA cycle stands out for its simplicity and efficiency.
This method makes it possible to understand problems in a structured way, identify their causes,
plan appropriate actions, and monitor the results obtained, creating a constant cycle of learning and
evolution. This work presents a case study developed by the maintenance team in a food industry,
where the challenge encountered was the recurrent cost with the change in the Noria chains,
equipment responsible for transporting the product throughout the production line. From the
application of the PDCA cycle, it was possible to analyze the history of occurrences, collect data,
identify the root cause of the problem and implement corrective actions. The monitoring of the
process showed positive results, with a 50% reduction in cost, an increase in the useful life of the
chains by more than 75%, and the fulfillment of the goals defined by the company. In addition, the
work demonstrated the possibility of replicating the methodology in other company processes,
strengthening the culture of continuous improvement within the organization.
Notes: Para Trabalho de Conclusão de Curso (TCC) é opcional a ficha catalográfica.2025-11-21T00:00:00ZModelagem Computacional de Escoamentos em Turbinas Francis Usando a Plataforma OpenFOAMhttps://repositorio.ufu.br/handle/123456789/480672026-01-27T06:19:55Z2025-12-19T00:00:00ZTitle: Modelagem Computacional de Escoamentos em Turbinas Francis Usando a Plataforma OpenFOAM
Abstract: This work presents the modeling and numerical simulation of incompressible
turbulent flow in a Francis turbine with a real geometry, based on the unit
installed at the Foz do Chapecó Hydropower Plant, using the OpenFOAM
software. A representative physical model of the machine is developed, the
mathematical model is formulated from the Navier--Stokes equations in the
URANS form with the k–ε turbulence model.
From the simulations, pressure and velocity fields are qualitatively
analyzed, showing behavior consistent with that expected for Francis turbines
and with reference results from the literature. Then, two approaches are
used to estimate the shaft power: one based on the First Law of
Thermodynamics, using averaged quantities at the inlet and outlet sections,
and another based on the rotor moment computed by the forces function of OpenFOAM. Powers of approximately 170.61 MW and 107 MW are obtained, respectively, both lower than the design
power of the unit 212 MW, which is discussed in terms of
geometric simplifications, boundary conditions and turbulence modeling
limitations. The results demonstrate the potential of Computational Fluid
Dynamics as an analysis tool for hydraulic turbines, while highlighting the
importance of careful modeling to achieve quantitative predictions closer to
the real behavior.2025-12-19T00:00:00Z