Análise de falhas em rolamentos por análise de vibração aplicado a aerogeradores

With the heavy use of bearings in various segments of the industry, there are a large number of necessary interruptions in industrial processes to perform maintenance on these devices, with the case study wind turbines. The growth of the wind energy sector, encouraged to conduct research that helps to solve this problem. To contribute to predictive maintenance has been carried out a signal analysis using techniques which allow detection and location of the problem in order to prevent accidents caused and losses due to unexpected equipment failures, whereas low system rotation complicates the detection of the failure. To work around this problem, there was the indication of standard signals for defects in the bearings, making diagnosis of possible failures. With this diagnosis can be performed predictive maintenance, identifying the failure of the system that were tested, such as the introduction of grains of sand in the bearing, wear on the outer race of the bearing and bearing rust. By processing signals it is possible to construct graphs developing a mapping of defects by different peaks in the frequency band.

Implementação de um Módulo de Supervisão para um Sistema de Detecção de Vazamentos em Dutos de Petróleo

The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

Localização e planejamento de caminhos para um robô humanóide e um robô escravo com rodas

This work presents the localization and path planning systems for two robots: a non-instrumented humanoid and a slave wheeled robot. The localization of wheeled robot is made using odometry information and landmark detection. These informations are fused using a Extended Kalman Filter. The relative position of humanoid is acquired fusing (using another Kalman Filter) the wheeled robot pose with the characteristics of the landmark on the back of humanoid. Knowing the wheeled robot position and the humanoid relative position in relation to it, we acquired the absolute position of humanoid. The path planning system was developed to provide the cooperative movement of the two robots,incorporating the visibility restrictions of the robotic system

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Reconhecimento de padrões de falhas em motores trifásicos utilizando redes neurais

This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern

Localização de um robô móvel usando odometria e marcos naturais

Several methods of mobile robot navigation request the mensuration of robot position and orientation in its workspace. In the wheeled mobile robot case, techniques based on odometry allow to determine the robot localization by the integration of incremental displacements of its wheels. However, this technique is subject to errors that accumulate with the distance traveled by the robot, making unfeasible its exclusive use. Other methods are based on the detection of natural or artificial landmarks present in the environment and whose location is known. This technique doesnt generate cumulative errors, but it can request a larger processing time than the methods based on odometry. Thus, many methods make use of both techniques, in such a way that the odometry errors are periodically corrected through mensurations obtained from landmarks. Accordding to this approach, this work proposes a hybrid localization system for wheeled mobile robots in indoor environments based on odometry and natural landmarks. The landmarks are straight lines de.ned by the junctions in environments floor, forming a bi-dimensional grid. The landmark detection from digital images is perfomed through the Hough transform. Heuristics are associated with that transform to allow its application in real time. To reduce the search time of landmarks, we propose to map odometry errors in an area of the captured image that possesses high probability of containing the sought mark

Estudo da detecção do DNA do papiloma vírus humano (HPV) e da expressão imuno-histoquímica de proteína do ciclo celular no carcinoma epidermóide oral

Oral squamous cell carcinoma (OSCC) is the most common malignancy in oral cavity and human papillomavirus (HPV) may have an important role in its development. The aim of this experiment was to investigate the HPV DNA and viral types in 90 cases of OSCC. Moreover, a comparative analysis between the cases of OSSC with and without HPV DNA was performed by using cell cycle markers p21 and pRb in order to detect a possible correlation of these proteins and HPV infection. DNA was extracted from paraffin embedded tissue and amplified by PCR (polymerase chain reaction) with primers PCO3+ e PCO4+ for a fragment of human β-globin gene. After this procedure, PCR for HPV DNA detection was realized using a pair of generic primers GP5+ e GP6+. Immunohistochemical study was performed by streptoavidin-biotin technique and antibodies against p21 and pRb proteins were employed. Eighty-eight cases were positive for human β-globin gene and HPV DNA was found in 26 (29.5%) of then. It could not be detected significant correlation between HPV and age, sex and anatomical sites of the lesion. The most prevalent viral type was HPV 18 (80.8%). Regarding the immunohistochemical analysis, it was detected significant association between HPV presence and pRb immunoexpression (p=0,044), nevertheless, the same was not observed in relation to p21 protein (p =0,416). It can be concluded that the low detection of HPV DNA in OSCC by the present experiment suggests a possible role of the virus in the development and progression in just a subset of this disease

Localização de faltas em linhas de transmissão usando morfologia matemática

This work an algorithm for fault location is proposed. It contains the following functions: fault detection, fault classification and fault location. Mathematical Morphology is used to process currents obtained in the monitored terminals. Unlike Fourier and Wavelet transforms that are usually applied to fault location, the Mathematical Morphology is a non-linear operation that uses only basic operation (sum, subtraction, maximum and minimum). Thus, Mathematical Morphology is computationally very efficient. For detection and classification functions, the Morphological Wavelet was used. On fault location module the Multiresolution Morphological Gradient was used to detect the traveling waves and their polarities. Hence, recorded the arrival in the two first traveling waves incident at the measured terminal and knowing the velocity of propagation, pinpoint the fault location can be estimated. The algorithm was applied in a 440 kV power transmission system, simulated on ATP. Several fault conditions where studied and the following parameters were evaluated: fault location, fault type, fault resistance, fault inception angle, noise level and sampling rate. The results show that the application of Mathematical Morphology in faults location is very promising

Estudo sobre a detecção de invariância de escala discreta em sistemas com criticalidade auto-organizada

Recent studies have shown evidence of log-periodic behavior in non-hierarchical systems. An interesting fact is the emergence of such properties on rupture and breakdown of complex materials and financial failures. These may be examples of systems with self-organized criticality (SOC). In this work we study the detection of discrete scale invariance or log-periodicity. Theoretically showing the effectiveness of methods based on the Fourier Transform of the log-periodicity detection not only with prior knowledge of the critical point before this point as well. Specifically, we studied the Brazilian financial market with the objective of detecting discrete scale invariance in Bovespa (Bolsa de Valores de S˜ao Paulo) index. Some historical series were selected periods in 1999, 2001 and 2008. We report evidence for the detection of possible log-periodicity before breakage, shown its applicability to the study of systems with discrete scale invariance likely in the case of financial crashes, it shows an additional evidence of the possibility of forecasting breakage

Metodologia de estimação de estados para tratamento de medições errôneas e registros não sincronizados em algoritmos de localização de faltas em linhas de transmissão

The performance of algorithms for fault location i n transmission lines is directly related to the accuracy of its input data. Thus, fa ctors such as errors in the line parameters, failures in synchronization of oscillographic recor ds and errors in measurements of voltage and current can significantly influence the accurac y of algorithms that use bad data to indicate the fault location. This work presents a new method ology for fault location in transmission lines based on the theory of state estimation in or der to determine the location of faults more accurately by considering realistic systematic erro rs that may be present in measurements of voltage and current. The methodology was implemente d in two stages: pre-fault and post- fault. In the first step, assuming non-synchronized data, the synchronization angle and positive sequence line parameters are estimated, an d in the second, the fault distance is estimated. Besides calculating the most likely faul t distance obtained from measurement errors, the variance associated with the distance f ound is also determined, using the errors theory. This is one of the main contributions of th is work, since, with the proposed algorithm, it is possible to determine a most likely zone of f ault incidence, with approximately 95,45% of confidence. Tests for evaluation and validation of the proposed algorithm were realized from actual records of faults and from simulations of fictitious transmission systems using ATP software. The obtained results are relevant to show that the proposed estimation approach works even adopting realistic variances, c ompatible with real equipments errors.

Implementação de um Módulo de Supervisão para um Sistema de Detecção de Vazamentos em Dutos de Petróleo

The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

Avaliação histomorfométrica do efeito do ultrasom pulsado nas falhas ósseas provocadas em fêmures de rato: estudo experimental

SILVA, J. S. P. Avaliação histomorfométrica do efeito do ultrasom pulsado nas falhas ósseas provocadas em fêmures de rato: estudo experimental . 2000. 85 f. Dissertação (Mestrado) – Faculdade de Medicina, Universidade de São Paulo. São Paulo, 2000.

Estudo do genoma do vírus causador da mionecrose infecciosa em camarões e desenvolvimento de métodos para detecção de diferentes variantes

Shrimp farming is one of the activities that contribute most to the growth of global aquaculture. However, this business has undergone significant economic losses due to the onset of viral diseases such as Infectious Myonecrosis (IMN). The IMN is already widespread throughout Northeastern Brazil and affects other countries such as Indonesia, Thailand and China. The main symptom of disease is myonecrosis, which consists of necrosis of striated muscles of the abdomen and cephalothorax of shrimp. The IMN is caused by infectious myonecrosis virus (IMNV), a non-enveloped virus which has protrusions along its capsid. The viral genome consists of a single molecule of double-stranded RNA and has two Open Reading Frames (ORFs). The ORF1 encodes the major capsid protein (MCP) and a potential RNA binding protein (RBP). ORF2 encodes a probable RNA-dependent RNA polymerase (RdRp) and classifies IMNV in Totiviridae family. Thus, the objective of this research was study the IMNV complete genome and encoded proteins in order to develop a system differentiate virus isolates based on polymorphisms presence. The phylogenetic relationship among some totivirus was investigated and showed a new group to IMNV within Totiviridae family. Two new genomes were sequenced, analyzed and compared to two other genomes already deposited in GenBank. The new genomes were more similar to each other than those already described. Conserved and variable regions of the genome were identified through similarity graphs and alignments using the four IMNV sequences. This analyze allowed mapping of polymorphic sites and revealed that the most variable region of the genome is in the first half of ORF1, which coincides with the regions that possibly encode the viral protrusion, while the most stable regions of the genome were found in conserved domains of proteins that interact with RNA. Moreover, secondary structures were predicted for all proteins using various softwares and protein structural models were calculated using threading and ab initio modeling approaches. From these analyses was possible to observe that the IMNV proteins have motifs and shapes similar to proteins of other totiviruses and new possible protein functions have been proposed. The genome and proteins study was essential for development of a PCR-based detection system able to discriminate the four IMNV isolates based on the presence of polymorphic sites

Análise de falhas em martelos oscilantes dos desfibradores da indústria sucroalcooleira da Região Norte-Nordeste

The failure of materials is always an unwelcome event for several reasons: human lives are put in danger, economic losses, and interference in the availability of products and services. Although the causes of failures and behaviour of materials can be known, the prevention of such a condition is difficult to be guaranteed. Among the failures, wear abrasion by the low voltage is the kind of failure that occurs in more equipment and parts industry. The Plants Sucroalcooleiras suffer significant losses because of such attrition, this fact that motivated their choice for the development of this work. For both, were considered failures in the swing hammers desfibradores stopped soon after the exchange provided in accordance with tonnage of cane processed, then were analyzed by the level of wear testing of rubber wheel defined by the standard ASTM G65-91.The failures were classified as to the origin of the cause and mechanism, moreover, were prepared with samples of welding procedures according to ASME code, sec. IX as well, using the technique of thermal spraying to analyze the performance of these materials produced in laboratories, and compares them with the solder used in the plant. It was observed that the bodies-of-proof prepared by the procedure described as welding, and the thermal spraying the results of losing weight have been minimized significantly compared to the preparations in the plant. This is because the use of techniques more appropriate and more controlled conditions of the parameters of welding. As for the thermal spraying, this technique has presented a satisfactory result, but requires the use of these coatings in the best condition for real affirmation of the results

Comportamento magnético de compósitos de matriz polimérica com adição de ferritas

Polymer matrix composites offer advantages for many applications due their combination of properties, which includes low density, high specific strength and modulus of elasticity and corrosion resistance. However, the application of non-destructive techniques using magnetic sensors for the evaluation these materials is not possible since the materials are non-magnetizable. Ferrites are materials with excellent magnetic properties, chemical stability and corrosion resistance. Due to these properties, these materials are promising for the development of polymer composites with magnetic properties. In this work, glass fiber / epoxy circular plates were produced with 10 wt% of cobalt or barium ferrite particles. The cobalt ferrite was synthesized by the Pechini method. The commercial barium ferrite was subjected to a milling process to study the effect of particle size on the magnetic properties of the material. The characterization of the ferrites was carried out by x-ray diffraction (XRD), field emission gun scanning electron microscopy (FEG-SEM) and vibrating sample magnetometry (VSM). Circular notches of 1, 5 and 10 mm diameter were introduced in the composite plates using a drill bit for the non-destructive evaluation by the technique of magnetic flux leakage (MFL). The results indicated that the magnetic signals measured in plates with barium ferrite without milling and cobalt ferrite showed good correlation with the presence of notches. The milling process for 12 h and 20 h did not contribute to improve the identification of smaller size notches (1 mm). However, the smaller particle size produced smoother magnetic curves, with fewer discontinuities and improved signal-to-noise ratio. In summary, the results suggest that the proposed approach has great potential for the detection of damage in polymer composites structures