A study on acoustic emission signal propagation of a small size multi-cylinder diesel engine

Acoustic emission has been found effective in offering earlier fault detection and improving identification capabilities of faults. However, the sensors are inherently uncalibrated. This paper presents a source to sensor paths calibration technique which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time domain, time-frequency domain, and the root mean square (RMS) energy. The results reveal how the RMS energy of a source propagates to the adjacent sensors. The findings lead to allocate the source and estimate its inferences to the adjacent sensor, and finally help to diagnose the small size diesel engines by minimising the crosstalk from multiple cylinders.

Statistical modelling of wind effects on signal propagation for wireless sensor networks

A wireless sensor network system must have the ability to tolerate harsh environmental conditions and reduce communication failures. In a typical outdoor situation, the presence of wind can introduce movement in the foliage. This motion of vegetation structures causes large and rapid signal fading in the communication link and must be accounted for when deploying a wireless sensor network system in such conditions. This thesis examines the fading characteristics experienced by wireless sensor nodes due to the effect of varying wind speed in a foliage obstructed transmission path. It presents extensive measurement campaigns at two locations with the approach of a typical wireless sensor networks configuration. The significance of this research lies in the varied approaches of its different experiments, involving a variety of vegetation types, scenarios and the use of different polarisations (vertical and horizontal). Non–line of sight (NLoS) scenario conditions investigate the wind effect based on different vegetation densities including that of the Acacia tree, Dogbane tree and tall grass. Whereas the line of sight (LoS) scenario investigates the effect of wind when the grass is swaying and affecting the ground-reflected component of the signal. Vegetation type and scenarios are envisaged to simulate real life working conditions of wireless sensor network systems in outdoor foliated environments. The results from the measurements are presented in statistical models involving first and second order statistics. We found that in most of the cases, the fading amplitude could be approximated by both Lognormal and Nakagami distribution, whose m parameter was found to depend on received power fluctuations. Lognormal distribution is known as the result of slow fading characteristics due to shadowing. This study concludes that fading caused by variations in received power due to wind in wireless sensor networks systems are found to be insignificant. There is no notable difference in Nakagami m values for low, calm, and windy wind speed categories. It is also shown in the second order analysis, the duration of the deep fades are very short, 0.1 second for 10 dB attenuation below RMS level for vertical polarization and 0.01 second for 10 dB attenuation below RMS level for horizontal polarization. Another key finding is that the received signal strength for horizontal polarisation demonstrates more than 3 dB better performances than the vertical polarisation for LoS and near LoS (thin vegetation) conditions and up to 10 dB better for denser vegetation conditions.

Fractional models in space for diffusive processes in heterogeneous media with applications in cell motility and electrical signal propagation

This work addresses fundamental issues in the mathematical modelling of the diffusive motion of particles in biological and physiological settings. New mathematical results are proved and implemented in computer models for the colonisation of the embryonic gut by neural cells and the propagation of electrical waves in the heart, offering new insights into the relationships between structure and function. In particular, the thesis focuses on the use of non-local differential operators of non-integer order to capture the main features of diffusion processes occurring in complex spatial structures characterised by high levels of heterogeneity.

SBS-based slow light in optical fibers: optimum design considerations for undistorted slow-light signal propagation in steady-state and transient regimes

SPIE

Solar signal propagation: the role of gravity waves and stratospheric sudden warmings

We use a troposphere‐stratosphere model of intermediate complexity to study the atmospheric response to an idealized solar forcing in the subtropical upper stratosphere during Northern Hemisphere (NH) early winter. We investigate two conditions that could influence poleward and downward propagation of the response: (1) the representation of gravity wave effects and (2) the presence/absence of stratospheric sudden warmings (SSWs). We also investigate how the perturbation influences the timing and frequency of SSWs. Differences in the poleward and downward propagation of the response within the stratosphere are found depending on whether Rayleigh friction (RF) or a gravity wave scheme (GWS) is used to represent gravity wave effects. These differences are likely related to differences in planetary wave activity in the GWS and RF versions, as planetary wave redistribution plays an important role in the downward and poleward propagation of stratospheric signals. There is also remarkable sensitivity in the tropospheric response to the representation of the gravity wave effects. It is most realistic for GWS. Further, tropospheric responses are systematically different dependent on the absence/presence of SSWs. When only years with SSWs are examined, the tropospheric signal appears to have descended from the stratosphere, while the signal in the troposphere appears disconnected from the stratosphere when years with SSWs are excluded. Different troposphere‐stratosphere coupling mechanisms therefore appear to be dominant for years with and without SSWs. The forcing does not affect the timing of SSWs, but does result in a higher occurrence frequency throughout NH winter. Quasi‐Biennial Oscillation effects were not included.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

Experimental Comparison of Bluetooth and WiFi Signal Propagation for Indoor Localisation

Systems for indoor positioning using radio technologies are largely studied due to their convenience and the market opportunities they offer. The positioning algorithms typically derive geographic coordinates from observed radio signals and hence good understanding of the indoor radio channel is required. In this paper we investigate several factors that affect signal propagation indoors for both Bluetooth and WiFi. Our goal is to investigate which factors can be disregarded and which should be considered in the development of a positioning algorithm. Our results show that technical factors such as device characteristics have smaller impact on the signal than multipath propagation. Moreover, we show that propagation conditions differ in each direction. We also noticed that WiFi and Bluetooth, despite operating in the same radio band, do not at all times exhibit the same behaviour.

Experimental investigation of radio signal propagation in scientific facilities for telerobotic applications

Understanding the radio signal transmission characteristics in the environment where the telerobotic application is sought is a key part of achieving a reliable wireless communication link between a telerobot and a control station. In this paper, wireless communication requirements and a case study of a typical telerobotic application in an underground facility at CERN are presented. Then, the theoretical and experimental characteristics of radio propagation are investigated with respect to time, distance, location and surrounding objects. Based on analysis of the experimental findings, we show how a commercial wireless system, such as Wi-Fi, can be made suitable for a case study application at CERN.

Neurite, a finite difference large scale parallel program for the simulation of the electrical signal propagation in neurites under mechanical loading

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, function of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells has only very recently been proposed (Jerusalem et al., 2013). In this paper, we present the implementation details of Neurite: the finite difference parallel program used in this reference. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite-explicit and implicit-were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between lectrophysiology and mechanics (Jerusalem et al., 2013). This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.

A Precharge-Absorbed DPL Logic for Reducing Early Propagation Effects on FPGA Implementations

In this paper, a new countermeasure against power and electromagnetic (EM) Side Channel Attacks (SCA) on FPGA implemented cryptographic algorithms is proposed. This structure mainly focuses on a critical vulnerability, Early Evaluation, also known as Early Propagation Effect (EPE), which exists in most conventional SCA-hardened DPL (Dual-rail with Precharge Logic) solutions. The main merit of this proposal is that the EPE can be effectively prevented by using a synchronized non regular precharge network, which maintains identical routing between the original and mirror parts, where costs and design complexity compared with previous EPE-resistant countermeasures are reduced, while security level is not sacrificed. Another advantage for our Precharge Absorbed(PA) - DPL method is that its Dual-Core style (independent architecture for true and false parts) could be generated using partial reconfiguration. This helps to get a dynamic security protection with better energy planning. That means system only keeps the true part which fulfills the normal en/decryption task in low security level, and reconfigures the false parts once high security level is required. A relatively limited clock speed is a compromise, since signal propagation is restricted to a portion of the clock period. In this paper, we explain the principles of PA-DPL and provide the guidelines to design this structure. We experimentally validate our methods in a minimized AES co-processor on Xilinx Virtex-5 board using electromagnetic (EM) attacks.

Radio propagation modeling and measurements for ZigBee based indoor wireless sensor networks

The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is difficult to estimate due to the irregularity of the physical environment and affects the WSN designers? decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to build the environment database accurately, which also significantly reduces time and efforts spent on non-radio propagation issue. The 3D ray tracing is developed by using kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. Signal propagation model is proposed for the ray tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of radio. Three different WSN deployments are realized in the indoor environment of an office and the results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in pre-simulation strategy and 3D ray searching scheme and is suitable for different indoor environments.

Effect of line of sight propagation on capacity of an indoor MIMO system

In this paper the performance of a multiple input multiple output (MIMO) wireless communication system operating in an indoor environment, featuring both line of sight (LOS) and non-line of sight (NLOS) signal propagation, is assessed. In the model the scattering objects are assumed to be uniformly distributed in an area surrounding the transmitting and receiving array antennas. Mutual coupling effects in the arrays are treated in an exact manner. However interactions with scattering objects are taken into account via a single bounce approach. Computer simulations are carried out for the system capacity for varying inter-element spacing in the receiving array for assumed values of LOS/NLOS power fraction and signal to noise ratio (SNR).

Investigations into the effect of LOS signal blocking on capacity of an indoor MIMO system

In indoor environments the properties of communication channel are affected by the presence of various objects which block the Line Of Sight signal propagation. For example, this occurs because of presence of movement of humans and furniture. In this paper, the effect of reflection and scattering due to the presence of such objects is studied with respect to the capacity of a multiple input multiple output (MIMO) wireless system. The carried out investigations are performed by applying a simple electromagnetic model, in which transmitting and receiving antennas of MIMO system, as well as signal blocking objects, are represented by wire dipoles. In order to provide a fair assessment, calculations of MIMO capacity are performed under both fixed transmitted power and fixed received power conditions.