Structural Health Monitoring (SHM) Using Strain Gauges, PVDF Film and Fiber Bragg Grating (FBG) Sensors: A Comparative Study

The term Structural Health Monitoring has gained wide acceptance in the recent pastas a means to monitor a structure and provide an early warning of an unsafe conditionusing real-time data. Utilization of structurally integrated, distributed sensors tomonitor the health of a structure through accurate interpretation of sensor signals andreal-time data processing can greatly reduce the inspection burden. The rapidimprovement of the Fiber Bragg Grating sensor technology for strain, vibration andacoustic emission measurements in recent times make them a feasible alternatives tothe traditional strain gauges transducers and conventional Piezoelectric sensors usedfor Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM).Optical fiber-based sensors offers advantages over conventional strain gauges, PVDFfilm and PZT devices in terms of size, ease of embedment, immunity fromelectromagnetic interference(EMI) and potential for multiplexing a number ofsensors. The objective of this paper is to demonstrate the feasibility of Fiber BraggGrating sensor and compare its utility with the conventional strain gauges and PVDFfilm sensors. For this purpose experiments are being carried out in the laboratory on acomposite wing of a mini air vehicle (MAV). In this paper, the results obtained fromthese preliminary experiments are discussed.

Ultrafast Raman loss spectroscopy (URLS): instrumentation and principle

In this paper, we report on the concept and the design principle of ultrafast Raman loss spectroscopy (URLS) as a structure-elucidating tool. URLS is an analogue of stimulated Raman scattering (SRS) but more sensitive than SRS with better signal-to-noise ratio. It involves the interaction of two laser sources, namely, a picosecond (ps) Raman pump pulse and a white-light (WL) continuum, with a sample, leading to the generation of loss signals on the higher energy (blue) side with respect to the wavelength of the Raman pump unlike the gain signal observed on the lower energy (red) side in SRS. These loss signals are at least 1.5 times more intense than the SRS signals. An experimental study providing an insight into the origin of this extra intensity in URLS as compared to SRS is reported. Furthermore, the very requirement of the experimental protocol for the signal detection to be on the higher energy side by design eliminates the interference from fluorescence, which appears on the red side. Unlike CARS, URLS signals are not precluded by the non-resonant background and, being a self-phase-matched process, URLS is experimentally easier. Copyright (C) 2011 John Wiley & Sons, Ltd.

Low-Complexity Detection in Large-Dimension MIMO-ISI Channels Using Graphical Models

In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov random field (MRF)-based graphical model with pairwise interaction, in conjunction with message damping, and 2) use of factor graph (FG)-based graphical model with Gaussian approximation of interference (GAI). The per-symbol complexities are O(K(2)n(t)(2)) and O(Kn(t)) for the MRF and the FG with GAI approaches, respectively, where K and n(t) denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large Kn(t). From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing Kn(t). Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of M-QAM symbol detection.

A power scalable receiver front-end at 2.4 GHz

We propose a Low Noise Amplifier (LNA) architecture for power scalable receiver front end (FE) for Zigbee. The motivation for power scalable receiver is to enable minimum power operation while meeting the run-time performance needed. We use simple models to find empirical relations between the available signal and interference levels to come up with required Noise Figure (NF) and 3rd order Intermodulation Product (IIP3) numbers. The architecture has two independent digital knobs to control the NF and IIP3. Acceptable input match while using adaptation has been achieved by using an Active Inductor configuration for the source degeneration inductor of the LNA. The low IF receiver front end (LNA with I and Q mixers) was fabricated in 130nm RFCMOS process and tested.

An Area-Efficient Noise-Adaptive Neural Amplifier in 130 nm CMOS Technology

Chronic recording of neural signals is indispensable in designing efficient brain–machine interfaces and to elucidate human neurophysiology. The advent of multichannel micro-electrode arrays has driven the need for electronics to record neural signals from many neurons. The dynamic range of the system can vary over time due to change in electrode–neuron distance and background noise. We propose a neural amplifier in UMC 130 nm, 1P8M complementary metal–oxide–semiconductor (CMOS) technology. It can be biased adaptively from 200 nA to 2 $mu{rm A}$, modulating input referred noise from 9.92 $mu{rm V}$ to 3.9 $mu{rm V}$. We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. Optimum sizing of the input transistors minimizes the accentuation of the input referred noise of the amplifier and obviates the need of large input capacitance. The amplifier achieves a noise efficiency factor of 2.58. The amplifier can pass signal from 5 Hz to 7 kHz and the bandwidth of the amplifier can be tuned for rejecting low field potentials (LFP) and power line interference. The amplifier achieves a mid-band voltage gain of 37 dB. In vitro experiments are performed to validate the applicability of the neural low noise amplifier in neural recording systems.

Transport and magnetic properties of Nd1-xPbxMnO3 single crystals

Transport and magnetic properties of flux-grown Nd1−xPbxMnO3 single crystals (x=0.15–0.5) are studied in the temperature range 300–77 K and 280–2 K, respectively. Magnetization measurements with a superconducting quantum interference device confirm a paramagnetic to ferromagnetic transition around 110, 121, 150, 160, and 178 K for x=0.15, 0.2, 0.3, 0.4, and 0.5, respectively. Four probe resistivity measurements at low temperatures show a monotonic increase for x=0.15 which represents a ferromagnetic insulating (FMI) phase. For Nd0.8Pb0.2MnO3 there is a slope change present in the resistivity profile at 127 K where metal to insulator transition (MI) sets in. For x=0.3 this MI transition is more prominent. However, both these samples have FMI phase at low temperature. When the concentration of lead increases (x>0.3) the sample displays a clear insulator to metal transition with a low temperature ferromagnetic metallic phase. On the basis of these measurements we have predicted the phase diagram of Nd1−xPbxMnO3. Magnetization measurements by a vibration sample magnetometer point out the appreciable differences between zero field cooled and field cooled profiles below the ferromagnetic to paramagnetic transition temperature for all x. These are indicative of magnetic frustration.

A PPCA based non-parametric modeling and retrieval of PD signal buried in excessive noise

The problem of on-line recognition and retrieval of relatively weak industrial signals such as partial discharges (PD), buried in excessive noise, has been addressed in this paper. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) due to the overlapping broad band frequency spectrum of PI and PD pulses. Therefore, on-line, onsite, PD measurement is hardly possible in conventional frequency based DSP techniques. The observed PD signal is modeled as a linear combination of systematic and random components employing probabilistic principal component analysis (PPCA) and the pdf of the underlying stochastic process is obtained. The PD/PI pulses are assumed as the mean of the process and modeled instituting non-parametric methods, based on smooth FIR filters, and a maximum aposteriori probability (MAP) procedure employed therein, to estimate the filter coefficients. The classification of the pulses is undertaken using a simple PCA classifier. The methods proposed by the authors were found to be effective in automatic retrieval of PD pulses completely rejecting PI.

A generalized network alignment for three-source three-destination multiple unicast networks with delays

The concept of interference alignment when extended to three-source three-destination instantaneous multiple unicast network for the case where, each source-destination pair has a min-cut of 1 and zero-interference conditions are not satisfied, is known to achieve a rate of half for every source-destination pair under certain conditions [6]. This was called network alignment. We generalize this concept of network alignment to three-source three-destination multiple unicast (3S-3D-MU) networks with delays, without making use of memory at the intermediate nodes (i.e., nodes other than the sources and destinations) and using time varying Local Encoding Kernels (LEKs). This achieves half the rate corresponding to the individual source-destination min-cut for some classes of 3S-3D-MU network with delays which do not satisfy the zero-interference conditions.

Implementation of a phase array diffuse optical tomographic imager

Diffuse optical tomography (DOT) using near-infrared (NIR) light is a promising tool for noninvasive imaging of deep tissue. This technique is capable of quantitative reconstructions of absorption coefficient inhomogeneities of tissue. The motivation for reconstructing the optical property variation is that it, and, in particular, the absorption coefficient variation, can be used to diagnose different metabolic and disease states of tissue. In DOT, like any other medical imaging modality, the aim is to produce a reconstruction with good spatial resolution and accuracy from noisy measurements. We study the performance of a phase array system for detection of optical inhomogeneities in tissue. The light transport through a tissue is diffusive in nature and can be modeled using diffusion equation if the optical parameters of the inhomogeneity are close to the optical properties of the background. The amplitude cancellation method that uses dual out-of-phase sources (phase array) can detect and locate small objects in turbid medium. The inverse problem is solved using model based iterative image reconstruction. Diffusion equation is solved using finite element method for providing the forward model for photon transport. The solution of the forward problem is used for computing the Jacobian and the simultaneous equation is solved using conjugate gradient search. The simulation studies have been carried out and the results show that a phase array system can resolve inhomogeneities with sizes of 5 mm when the absorption coefficient of the inhomogeneity is twice that of the background tissue. To validate this result, a prototype model for performing a dual-source system has been developed. Experiments are carried out by inserting an inhomogeneity of high optical absorption coefficient in an otherwise homogeneous phantom while keeping the scattering coefficient same. The high frequency (100 MHz) modulated dual out-of-phase laser source light is propagated through the phantom. The interference of these sources creates an amplitude null and a phase shift of 180° along a plane between the two sources with a homogeneous object. A solid resin phantom with inhomogeneities simulating the tumor is used in our experiment. The amplitude and phase changes are found to be disturbed by the presence of the inhomogeneity in the object. The experimental data (amplitude and the phase measured at the detector) are used for reconstruction. The results show that the method is able to detect multiple inhomogeneities with sizes of 4 mm. The localization error for a 5 mm inhomogeneity is found to be approximately 1 mm.

Weakening of charge order and antiferromagnetic to ferromagnetic switch over in Pr0.5Ca0.5MnO3 nanowires

We have prepared crystalline nanowires (diameter ∼ 50 nm, length ∼ a few microns) of the charge-ordering manganite Pr0.5Ca0.5MnO3 using a low reaction temperature hydrothermal method and characterized them using x-ray diffraction, transmission electron microscopy, superconducting quantum interference device (SQUID) magnetometry and electron magnetic resonance measurements. While the bulk sample shows a charge ordering transition at 245 K and an antiferromagnetic transition at 175 K, SQUID magnetometry and electron magnetic resonance experiments reveal that in the nanowires phase, a ferromagnetic transition occurs at ∼ 105 K. Further, the antiferromagnetic transition disappears and the charge ordering transition is suppressed. This result is particularly significant since the charge order in Pr0.5Ca0.5MnO3 is known to be very robust, magnetic fields as high as 27 T being needed to melt it.

Unified Spectral Efficiency Analysis of Cellular Systems with Channel-Aware Schedulers

Spectral efficiency is a key characteristic of cellular communications systems, as it quantifies how well the scarce spectrum resource is utilized. It is influenced by the scheduling algorithm as well as the signal and interference statistics, which, in turn, depend on the propagation characteristics. In this paper we derive analytical expressions for the short-term and long-term channel-averaged spectral efficiencies of the round robin, greedy Max-SINR, and proportional fair schedulers, which are popular and cover a wide range of system performance and fairness trade-offs. A unified spectral efficiency analysis is developed to highlight the differences among these schedulers. The analysis is different from previous work in the literature in the following aspects: (i) it does not assume the co-channel interferers to be identically distributed, as is typical in realistic cellular layouts, (ii) it avoids the loose spectral efficiency bounds used in the literature, which only considered the worst case and best case locations of identical co-channel interferers, (iii) it explicitly includes the effect of multi-tier interferers in the cellular layout and uses a more accurate model for handling the total co-channel interference, and (iv) it captures the impact of using small modulation constellation sizes, which are typical of cellular standards. The analytical results are verified using extensive Monte Carlo simulations.

BER Analysis of Uplink OFDMA in the Presence of Carrier Frequency and Timing Offsets on Rician Fading Channels

In orthogonal frequency-division multiple access (OFDMA) on the uplink, the carrier frequency offsets (CFOs) and/or timing offsets (TOs) of other users with respect to a desired user can cause multiuser interference (MUI). Analytically evaluating the effect of these CFO/TO-induced MUI on the bit error rate (BER) performance is of interest. In this paper, we analyze the BER performance of uplink OFDMA in the presence of CFOs and TOs on Rician fading channels. A multicluster multipath channel model that is typical in indoor/ultrawideband and underwater acoustic channels is considered. Analytical BER expressions that quantify the degradation in BER due to the combined effect of both CFOs and TOs in uplink OFDMA with M-state quadrature amplitude modulation (QAM) are derived. Analytical and simulation BER results are shown to match very well. The derived BER expressions are shown to accurately quantify the performance degradation due to nonzero CFOs and TOs, which can serve as a useful tool in OFDMA system design.

A novel free floating accelerometer force balance system for shock tunnel applications

In order to overcome the interference of the model mounting system with the external aerodynamics of the body during shock tunnel testing, a new free floating internally mountable balance system that ensures unrestrained model motion during testing has been designed, fabricated and tested. Minimal friction ball bearings are used for ensuring the free floating condition of the model during tunnel testing. The drag force acting on a blunt leading edge flat plate at hypersonic Mach number has been measured using the new balance system. Finite element model (FEM) and CFD are exhaustively used in the design as well as for calibrating the new balance system. The experimentally measured drag force on the blunt leading edge flat plate at stagnation enthalpy of 0.7 and 1.2 MJ/kg and nominal Mach number of 5.75 matches well with FEM results. The concept can also be extended for measuring all the three fundamental aerodynamic forces in short duration test facilities like free piston driven shock tunnels.

A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.

Enhancing Speedup in Network Processing Applications by Exploiting Instruction Reuse with Flow Aggregation

Instruction reuse is a microarchitectural technique that improves the execution time of a program by removing redundant computations at run-time. Although this is the job of an optimizing compiler, they do not succeed many a time due to limited knowledge of run-time data. In this paper we examine instruction reuse of integer ALU and load instructions in network processing applications. Specifically, this paper attempts to answer the following questions: (1) How much of instruction reuse is inherent in network processing applications?, (2) Can reuse be improved by reducing interference in the reuse buffer?, (3) What characteristics of network applications can be exploited to improve reuse?, and (4) What is the effect of reuse on resource contention and memory accesses? We propose an aggregation scheme that combines the high-level concept of network traffic i.e. "flows" with a low level microarchitectural feature of programs i.e. repetition of instructions and data along with an architecture that exploits temporal locality in incoming packet data to improve reuse. We find that for the benchmarks considered, 1% to 50% of instructions are reused while the speedup achieved varies between 1% and 24%. As a side effect, instruction reuse reduces memory traffic and can therefore be considered as a scheme for low power.