Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

Efficiency and feasibility of product disassembly: A case-based study

The productivity associated with commonly available disassembly methods today seldomly makes disassembly the preferred end-of-life solution for massive take back product streams. Systematic reuse of parts or components, or recycling of pure material fractions are often not achievable in an economically sustainable way. In this paper a case-based review of current disassembly practices is used to analyse the factors influencing disassembly feasibility. Data mining techniques were used to identify major factors influencing the profitability of disassembly operations. Case characteristics such as involvement of the product manufacturer in the end-of-life treatment and continuous ownership are some of the important dimensions. Economic models demonstrate that the efficiency of disassembly operations should be increased an order of magnitude to assure the competitiveness of ecologically preferred, disassembly oriented end-of-life scenarios for large waste of electric and electronic equipment (WEEE) streams. Technological means available to increase the productivity of the disassembly operations are summarized. Automated disassembly techniques can contribute to the robustness of the process, but do not allow to overcome the efficiency gap if not combined with appropriate product design measures. Innovative, reversible joints, collectively activated by external trigger signals, form a promising approach to low cost, mass disassembly in this context. A short overview of the state-of-the-art in the development of such self-disassembling joints is included. (c) 2008 CIRP.

Assessment of the Performance of Acoustic and Mass Balance Methods for Leak Detection in Pipelines for Transporting Liquids

On-line leak detection is a main concern for the safe operation of pipelines. Acoustic and mass balance are the most important and extensively applied technologies in field problems. The objective of this work is to compare these leak detection methods with respect to a given reference situation, i.e., the same pipeline and monitoring signals acquired at the inlet and outlet ends. Experimental tests were conducted in a 749 m long laboratory pipeline transporting water as the working fluid. The instrumentation included pressure transducers and electromagnetic flowmeters. Leaks were simulated by opening solenoid valves placed at known positions and previously calibrated to produce known average leak flow rates. Results have clearly shown the limitations and advantages of each method. It is also quite clear that acoustics and mass balance technologies are, in fact, complementary. In general, an acoustic leak detection system sends out an alarm more rapidly and locates the leak more precisely, provided that the rupture of the pipeline occurs abruptly enough. On the other hand, a mass balance leak detection method is capable of quantifying the leak flow rate very accurately and of detecting progressive leaks.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

Experimental results on the nonlinear H(infinity) control via quasi-LPV representation and game theory for wheeled mobile robots

In this paper, nonlinear dynamic equations of a wheeled mobile robot are described in the state-space form where the parameters are part of the state (angular velocities of the wheels). This representation, known as quasi-linear parameter varying, is useful for control designs based on nonlinear H(infinity) approaches. Two nonlinear H(infinity) controllers that guarantee induced L(2)-norm, between input (disturbances) and output signals, bounded by an attenuation level gamma, are used to control a wheeled mobile robot. These controllers are solved via linear matrix inequalities and algebraic Riccati equation. Experimental results are presented, with a comparative study among these robust control strategies and the standard computed torque, plus proportional-derivative, controller.

Low-Intensity Electrical Stimulation Counteracts the Effects of Ovariectomy on Bone Tissue of Rats: Effects on Bone Microarchitecture, Viability of Osteocytes, and Nitric Oxide Expression

Low Intensity Electrical Stimulation (LIES) has been used for bone repair, but little is known about its effects on bone after menopause. Osteocytes probably play a role in mediating this physical stimulus and they could act as transducers through the release of biochemical signals, such as nitric oxide (NO). The aim of the present study was to investigate the effects of LIES on bone structure and remodeling, NOS expression and osteocyte viability in ovariectomized (OVX) rats. Thirty rats (200-220 g) were divided into 3 groups: SHAM, OVX, and OVX subjected to LIES (OVX + LIES) for 12 weeks. Following the protocol, rats were sacrificed and tibias were collected for histomorphometric analysis and immunohistochemical detection of endothelial NO synthase (eNOS), inducible NOS (iNOS), and osteocyte apoptosis (caspase-3 and TUNEL). OVX rats showed significant (p < 0.05 vs. SHAM) decreased bone volume (10% vs. 25%) and trabecular number (1.7 vs. 3.9), and increased eroded surfaces (4.7% vs. 3.2%) and mineralization surfaces (15.9% vs. 7.7%). In contrast, after LIES, all these parameters were significantly different from OVX but not different from SHAM. eNOS and iNOS were similarly expressed in subperiosteal regions of tibiae cortices of SHAM, not expressed in OVX, and similarly expressed in OVX + LIES when compared to SHAM. In OVX, the percentage of apoptotic osteocytes (24%) was significantly increased when compared to SHAM (11%) and OVX + LIES (8%). Our results suggest that LIES counteracts some effects of OVX on bone tissue preserving bone structure and microarchitecture, iNOS and eNOS expression, and osteocyte viability.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

Experimental analysis of wheel/workpiece dynamic interactions in grinding

The aim of this work is to study the wheel/workpiece dynamic interactions in high-speed grinding using vitrified CBN wheel and DTG (difficult to grind) work materials. This problem is typical in the grinding of engine valve heads. The influence of tangential force per abrasive grain was investigated as an important control variable for the determination of G ratio. Experiments were carried out to observe the influence of vibrations in the wheel wear. The measurements of acoustic emission (AE) and vibration signals helped in identifying the correlation between the dynamic interactions (produced by forced random excitation) and the wheel wear. The wheel regenerative chatter phenomenon was observed by using the wheel mapping technique. (c) 2008 CIRP.

Fault-Location System for Multiterminal Transmission Lines

This research presents the development and implementation in a computational routine of algorithms for fault location in multiterminal transmission lines. These algorithms are part of a fault-location system, which is capable of correctly identifying the fault point based on voltage and current phasor quantities, calculated by using measurements of voltage and current signals from intelligent electronic devices, located on the transmission-line terminals. The algorithms have access to the electrical parameters of the transmission lines and to information about the transformers loading and their connection type. This paper also presents the development of phase component models for the power system elements used by the fault-location algorithms.

Ultrasound, eddy current and magnetic Barkhausen noise as tools for sigma phase detection on a UNS S31803 duplex stainless steel

Sigma phase is a deleterious one which can be formed in duplex stainless steels during heat treatment or welding. Aiming to accompany this transformation, ferrite and sigma percentage and hardness were measured on samples of a UNS S31803 duplex stainless steel submitted to heat treatment. These results were compared to measurements obtained from ultrasound and eddy current techniques, i.e., velocity and impedance, respectively. Additionally, backscattered signals produced by wave propagation were acquired during ultrasonic inspection as well as magnetic Barkhausen noise during magnetic inspection. Both signal types were processed via a combination of detrended-fluctuation analysis (DFA) and principal component analysis (PCA). The techniques used were proven to be sensitive to changes in samples related to sigma phase formation due to heat treatment. Furthermore, there is an advantage using these methods since they are nondestructive. (C) 2010 Elsevier B.V. All rights reserved.

NDT flaw mapping of steel surfaces by continuous magnetic Barkhausen noise: Volumetric flaw detection case

This paper reports the use of a non-destructive, continuous magnetic Barkhausen noise (CMBN) technique to investigate the size and thickness of volumetric defects, in a 1070 steel. The magnetic behavior of the used probe was analyzed by numerical simulation, using the finite element method (FEM). Results indicated that the presence of a ferrite coil core in the probe favors MBN emissions. The samples were scanned with different speeds and probe configurations to determine the effect of the flaw on the CMBN signal amplitude. A moving smooth window, based on a second-order statistical moment, was used for analyzing the time signal. The results show the technique`s good repeatability, and high capacity for detection of this type of defect. (C) 2009 Elsevier Ltd. All rights reserved.

A study of plastic deformation around a defect using the magnetic Barkhausen noise in ASTM 36 steel

The present work presents the measurements of the magnetic Barkhausen noise (MBN) in ASTM 36 steel samples around a pit under plastic deformation. The contour maps obtained from these Barkhausen noise measurements are compared with the finite element analysis of the ideal plastic deformation. Also, a parameter of the Barkhausen signal to detect the plastic deformation around the pit in ASTM 36 steel is obtained. Additionally to that, we propose another MBN parameter to estimate the pit width using the Barkhausen noise. (c) 2007 Elsevier Ltd. All rights reserved.

Impact of plastic deformation on magnetoacoustic properties of Fe-2%Si alloy

The paper presents the results of a complementary study including magnetic hysteresis loops B(H), magnetic Barkhausen noise (MBN) and magnetoacoustic emission (MAE) signals measurements for plastically deformed Fe-2%Si samples. The investigated samples had been plastically deformed with plastic strain level (epsilon(p)) up to 8%. The properties of B(H) loops are quantified using the coercivity H(C) and maximum differential permeability mu(rmax) as parameters. The MBN and MAE voltage signals were analysed by means of rms-like voltage (Ub and Ua, respectively) envelopes, plotted as a function of applied field strength. Integrals of the Ub and Ua voltages over half of a period of magnetization were then calculated. It has been found that He and integrals of Ub increase, while mu(rmax) decreases monotonically with increasing epsilon(p). The MAE (Ua) peak voltage at first decreases, then peaks at epsilon(p) approximate to 1.5% and finally decreases again. The integral of the Ua voltage at first increases for low epsilon(p) and then decreases for epsilon(p) > 1.5%. All those various dependence types suggest the possibility of detection of various stages of microstructure change. The above-mentioned results are discussed qualitatively in the paper. Some modelling of the discussed dependency is also presented. (C) 2008 Elsevier Ltd. All rights reserved.

An In-Depth Study of the Barkhausen Emission Signal Properties of the Plastically Deformed Fe-2%Si Alloy

This paper presents the results of the in-depth study of the Barkhausen effect signal properties for the plastically deformed Fe-2%Si samples. The investigated samples have been deformed by cold rolling up to plastic strain epsilon(p) = 8%. The first approach consisted of time-domain-resolved pulse and frequency analysis of the Barkhausen noise signals whereas the complementary study consisted of the time-resolved pulse count analysis as well as a total pulse count. The latter included determination of time distribution of pulses for different threshold voltage levels as well as the total pulse count as a function of both the amplitude and the duration time of the pulses. The obtained results suggest that the observed increase in the Barkhausen noise signal intensity as a function of deformation level is mainly due to the increase in the number of bigger pulses.

Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.