Signature analysis on wheel-rail interaction for rail defect detection

Fibre Bragg Grating (FBG) sensors have been installed along an existing line for the purposes of train detection and weight measurement. The results show fair accuracy and high resolution on the vertical force acted on track when the train wheels are rolling upon. While the sensors are already in place and data is available, further applications beyond train detection are explored. This study presents the analysis on the unique signatures from the data collected to characterise wheel-rail interaction for rail defect detection. Focus of this first stage of work is placed on the repeatability of signals from the same wheel-rail interactions while the rail is in healthy state. Discussions on the preliminary results and hence the feasibility of this condition monitoring application, as well as technical issues to be addressed in practice, are given.

Vibration Signature Analysis Using Artificial Neural Networks

Damage detection by measuring and analyzing vibration signals in a machine component is an established procedure in mechanical and aerospace engineering. This paper presents vibration signature analysis of steel bridge structures in a nonconventional way using artificial neural networks (ANN). Multilayer perceptrons have been adopted using the back-propagation algorithm for network training. The training patterns in terms of vibration signature are generated analytically for a moving load traveling on a trussed bridge structure at a constant speed to simulate the inspection vehicle. Using the finite-element technique, the moving forces are converted into stationary time-dependent force functions in order to generate vibration signals in the structure and the same is used to train the network. The performance of the trained networks is examined for their capability to detect damage from unknown signatures taken independently at one, three, and five nodes. It has been observed that the prediction using the trained network with single-node signature measurement at a suitability chosen location is even better than that of three-node and five-node measurement data.

GYROSONICS: SIGNATURE ANALYSIS AND REDUCED-ORDER MODELS

In this paper, the authors study the structure of a novel binaural sound with a certain phase and amplitude modulation and the response to this excitation when it is applied to natural rewarding circuit of human brain through auditory neural pathways. This novel excitation, also referred to as gyrosonic excitation in this work, has been found to have interesting effects such as stabilization effects on the left and right hemispheric brain signaling as captured by Galvanic Skin Resistance (GSR) measurements, control of cardiac rhythms (observed from ECG signals), mitigation of psychosomatic syndrome, and mitigation of migraine pain. Experimental data collected from human subjects are presented, and these data are examined to categorize the extent of systems disorder and reinforcement reward due to the gyrosonic stimulus. A multi-path reduced-order model has been developed to analyze the GSR signals. The filtered results are indicative of complicated reinforcing reward patterns due to the gyrosonic stimulation when it is used as a control input for patients with psychosomatic and cardiac disorders.

Stall warning by blade pressure signature analysis

At low mass flow rates axial compressors suffer from flow instabilities leading to stall and surge. The inception process of these instabilities has been widely researched in the past - primarily with the aim of predicting or averting stall onset. In recent times, attention has shifted to conditions well before stall and has focussed on the level of irregularity in the blade passing signature in the rotor tip region. In general, this irregularity increases in intensity as the flow rate through the compressor is reduced. Attempts have been made to develop stall warning/avoidance procedures based on the level of the flow irregularity, but little effort has been made to characterise the irregularity, or to understand its underlying causes. Work on this project has revealed for the first time that the increase in irregularity in the blade passing signature is highly dependent on both tip-clearance and eccentricity. In a compressor with small, uniform, tip-clearance, the increase in blade passing irregularity which accompanies a reduction in flow rate will be modest. If the tip-clearance is enlarged, however, there will be a sharp rise in irregularity at all circumferential locations. In a compressor with eccentric tip-clearance, the increase in irregularity will only occur in the part of the annulus where the tip-clearance is largest, regardless of the average clearance level. In this paper, some attention is also given to the question of whether this irregularity observed in the pre-stall flow field is due to random turbulence, or to some form of coherent flow structure. Detailed flow measurements reveal that the latter is the case. From these findings, it is clear that a stall warning system based on blade passing signature irregularity will not be viable in an aero-engine where tip-clearance size and eccentricity change during each flight cycle and over the life of the compressor. Copyright © 2011 by ASME.

Stall Warning by Blade Pressure Signature Analysis

At low mass flow rates, axial compressors suffer from flow instabilities leading to stall and surge. The inception process of these instabilities has been widely researched in the past---primarily with the aim of predicting or averting stall onset. In recent times, attention has shifted to conditions well before stall and has focused on the level of irregularity in the blade passing signature in the rotor tip region. In general, the irregularity increases in intensity as the flow rate through the compressor is reduced. Attempts have been made to develop stall warning/avoidance procedures based on the level of flow irregularity, but little effort has been made to characterize the irregularity itself, or to understand its underlying cause. Work on this project has revealed for the first time that the increase in irregularity in the blade passing signature is highly dependent on both tip-clearance size and eccentricity. In a compressor with small, uniform, tip-clearance, the increase in blade passing irregularity that accompanies a reduction in flow rate will be modest. If the tip-clearance is enlarged, however, there will be a sharp rise in irregularity at all circumferential locations. In a compressor with eccentric tip-clearance, the increase in irregularity will only occur in the part of the annulus where the tip-clearance is largest, regardless of the average clearance level. In this paper, some attention is also given to the question of whether the irregularity observed in the prestall flow field is due to random turbulence or to some form of coherent flow structure. Detailed flow measurements reveal that the latter is the case. From these findings, it is clear that a stall warning system based on blade passing signature irregularity would be difficult to implement in an aero-engine where tip-clearance size and eccentricity change during each flight cycle and over the life of the compressor. © 2013 American Society of Mechanical Engineers.

An attack signature model to computer security intrusion detection

Internal and external computer network attacks or security threats occur according to standards and follow a set of subsequent steps, allowing to establish profiles or patterns. This well-known behavior is the basis of signature analysis intrusion detection systems. This work presents a new attack signature model to be applied on network-based intrusion detection systems engines. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using this new model, the process of storing and analyzing information about intrusion signatures for further use by an IDS become a less difficult and standardized process.

Acoustic emission for diesel engine monitoring: A review and preliminary

Vibration analysis has been a prime tool in condition monitoring of rotating machines, however, its application to internal combustion engines remains a challenge because engine vibration signatures are highly non-stationary that are not suitable for popular spectrum-based analysis. Signal-to-noise ratio is a main concern in engine signature analysis due to severe background noise being generated by consecutive mechanical events, such as combustion, valve opening and closing, especially in multi-cylinder engines. Acoustic Emission (AE) has been found to give excellent signal-to-noise ratio allowing discrimination of fine detail of normal or abnormal events during a given cycle. AE has been used to detect faults, such as exhaust valve leakage, fuel injection behaviour, and aspects of the combustion process. This paper presents a review of AE application to diesel engine monitoring and preliminary investigation of AE signature measured on an 18-cylinder diesel engine. AE is compared with vibration acceleration for varying operating conditions: load and speed. Frequency characteristics of AE from those events are analysed in time-frequency domain via short time Fourier trasform. The result shows a great potential of AE analysis for detection of various defects in diesel engines.

Generalized model for infrared perception from an engine exhaust

A comprehensive scheme has been developed for the prediction of radiation from engine exhaust and its incidence on an arbitrarily located sensor. Existing codes have been modified for the simulation of flows inside nozzles and jets. A novel view factor computation scheme has been applied for the determination of the radiosities of the discrete panels of a diffuse and gray nozzle surface. The narrowband model has been used to model the radiation from the gas inside the nozzle and the nonhomogeneous jet. The gas radiation from the nozzle inclusive of nozzle surface radiosities have been used as boundary conditions on the jet radiation. Geometric modeling techniques have been developed to identify and isolate nozzle surface panels and gas columns of the nozzle and jet to determine the radiation signals incident on the sensor. The scheme has been validated for intensity and heat flux predictions, and some useful results of practical importance have been generated to establish its viability for infrared signature analysis of jets.

Diagnóstico de avarias em motores elétricos

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

El perfil criminal del asesino en serie colombiano desde la perspectiva psicodinámica. Una revisión de literatura

El objetivo de la presente investigación consiste en describir las características de un asesino en serie colombiano desde la perspectiva psicodinámica. En este sentido, el abordaje teórico realizado en este trabajo se compone inicialmente de una concepción de asesinos en serie, posteriormente se hace una revisión acerca de las bases biológicas y los factores sociales del homicida serial, igualmente, se explican tres teorías psicodinámicas a trabajar (Sigmund Freud y Erick Erickson). Finalmente, se hace mención dentro de la investigación a la comparación casuística de los asesinos en serie, teniendo en cuenta a cuatro asesinos en serie mediante el abordaje psicodinámico. Por otra parte, a nivel metodológico, el tipo de estudio realizado es descriptivo con un corte cualitativo y un diseño no experimental, basado en la revisión de fuentes bibliográficas. Como producto se pretende hacer una aproximación al perfil correspondiente de la personalidad de un asesino en serie colombiano mediante las teorías psicodinámicas.

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

Interações tróficas entre espécies pelágicas do Atlântico Sudoeste: utilizando isótopos estáveis e inferência bayesiana

Pós-graduação em Ciências Biológicas (Zoologia) - IBRC

Selection signatures in Shetland ponies.

Shetland ponies were selected for numerous traits including small stature, strength, hardiness and longevity. Despite the different selection criteria, Shetland ponies are well known for their small stature. We performed a selection signature analysis including genome-wide SNPs of 75 Shetland ponies and 76 large-sized horses. Based upon this dataset, we identified a selection signature on equine chromosome (ECA) 1 between 103.8 Mb and 108.5 Mb. A total of 33 annotated genes are located within this interval including the IGF1R gene at 104.2 Mb and the ADAMTS17 gene at 105.4 Mb. These two genes are well known to have a major impact on body height in numerous species including humans. Homozygosity mapping in the Shetland ponies identified a region with increased homozygosity between 107.4 Mb and 108.5 Mb. None of the annotated genes in this region have so far been associated with height. Thus, we cannot exclude the possibility that the identified selection signature on ECA1 is associated with some trait other than height, for which Shetland ponies were selected.

Dynamics of halocarbons in coastal surface waters during short term mesocosm experiments

The aim of the present study was to evaluate the influence of different light quality, especially ultraviolet radiation (UVR), on the dynamics of volatile halogenated organic compounds (VHOCs) at the sea surface. Short term experiments were conducted with floating gas-tight mesocosms of different optical qualities. Six halocarbons (CH3I, CHCl3, CH2Br2, CH2ClI, CHBr3 and CH2I2), known to be produced by phytoplankton, together with a variety of biological and environmental variables were measured in the coastal southern Baltic Sea and in the Raunefjord (North Sea). These experiments showed that ambient levels of UVR have no significant influence on VHOC dynamics in the natural systems. We attribute it to the low radiation doses that phytoplankton cells receive in a normal turbulent surface mixed layer. The VHOC concentrations were influenced by their production and removal processes, but they were not correlated with biological or environmental parameters investigated. Diatoms were most likely the dominant biogenic source of VHOCs in the Baltic Sea experiment, whereas in the Raunefjord experiment macroalgae probably contributed strongly to the production of VHOCs. The variable stable carbon isotope signatures (d13C values) of bromoform (CHBr3) also indicate that different autotrophic organisms were responsible for CHBr3 production in the two coastal environments. In the Raunefjord, despite strong daily variations in CHBr3 concentration, the carbon isotopic ratio was fairly stable with a mean value of -26 per mil. During the declining spring phytoplankton bloom in the Baltic Sea, the d13C values of CHBr3 were enriched in 13C and showed noticeable diurnal changes (-12 per mil ± 4). These results show that isotope signature analysis is a useful tool to study both the origin and dynamics of VHOCs in natural systems.